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Pipeline run

ac7975a9-9b3e-4561-848a-8f25472dc25f

Pipeline LLM cost (USD)
API 1: $0.0091 API 2: $0.0004 API 3: $0.0000 Total: $0.0095

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Test Automation / QE Engineering
Builds and reviews Python/pytest/Bash automation and QE infrastructure for storage systems, designs test plans/cases, runs test environments, and drives faster, more reliable testing with defect/status coordination across teams.
""develop software automation tools and infrastructure to enable repeatable and extensible test""
Tech stack maturity
Mainstream Modern
The skill mix of bash, code review, pytest, and Python is characteristic of a modern, widely adopted testing/tooling stack rather than cloud-native or legacy-only environments.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.20 / 5
· Title match
Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): AI
Evidence — skills matched in JD (19)
Python pytest Bash Functional Testing Structural Testing Test Automation Code Review Ansible C++ Go Agile Distributed Systems Concurrent Systems Lustre GPFS NVM Storage Distributed Key-Value Storage Object Storage High Performance Computing
Skill cluster (5 dimension groups, role-scoped)
C# and .NET Languages
C++
Go Language and Toolchain
Go
Performance and Scalability Tuning
Distributed Systems
Python Programming
Python
Cross-cutting / unaligned
pytest Bash Functional Testing Structural Testing Test Automation Code Review Ansible Agile Concurrent Systems Lustre GPFS NVM Storage Distributed Key-Value Storage Object Storage High Performance Computing
Show KRA description ↓
We are looking for a Senior Software Engineer in Test for our Infinia Storage engineering team who will design, build and deliver strategic and modern components of the Quality Engineering process and infrastructure, for the Infinia engineering organization. This crucial member of QE will rely on their software engineering skills to develop software automation tools and infrastructure to enable repeatable and extensible test and customer-focused simulated scenarios, for all phases of testing data storage/intelligence subsystems. They will evaluate, recommend, and implement methods to expedite testing cycles and improve overall test and product quality. • Drive design discussions, build prototypes and contribute to delivering high quality Test and Engineering Velocity solutions • Conduct code reviews and improve scalability, stability and reliability of test • Collaborate with teammates as a unified group of passionate engineers in an outcome- oriented environment. • Design test plans, and test cases, leveraging test automation • Review acceptance criteria, reviews test cases and test automation code, sets up environments, and communicates regularly to project team on defects, issues, and QE status • Coordinate testing effort with other project teams across the globe • Work closely with the Test Architect, Test Leads, Test Engineers and Developers/Designers to understand and provide solutions for any challenges that could impact the delivery of test automation. • Participation in a team on-call rotation providing seven-day week out of hours coverage, including the provision of after-hours and weekend support work when required. • BS/MS/Ph.D in Computer Science, Computer Engineering, Statistics, Mathematics or equivalent degree/experience. • 6+ years of Software Development or Software Development for Test experience, preferably in technology domains involving distributed concurrent systems, data or storage systems. • Experience with QE methodology, functional and structural testing techniques (Agile a plus) • Must have experience in python or related modern high-level languages, pytest and bash. Experience in ansible is a plus. • Good problem solving, organizational, interpersonal and team skills • Ability to work seamlessly as part of a multi-site, multicultural engineering team • Self-motivated, passionate, and driven to achieve committed milestones • Strong team player with excellent written and verbal skills • Ability to work in a fast-paced development environment with a broad scope of evolving responsibilities • Ability to read and understand coding languages and logic including C++ and GoLang • Knowledge of parallel file system solutions (Lustre, GPFS), NVM storage technology or distributed key-value storage systems • Knowledge of Object Storage and its usage • High Performance Computing system installation and management is helpful to perform day-to-day activities for this role

Signals

Skill python-backend-developer
0.29
Alias
KRA angular-frontend-developer
0.57

Post-classification

Centroidupdated · n=14
Alias collision log
New-role queue
New skills captured10
New KRA capturedyes

Captured for admin review

Functional Testing primary SDET pending
Structural Testing primary SDET pending
Test Automation primary SDET pending
Concurrent Systems SDET pending
Lustre SDET pending
GPFS SDET pending
NVM Storage SDET pending
Distributed Key-Value Storage SDET pending
Object Storage SDET pending
High Performance Computing SDET pending
R&R fragment (sim 0.00) SDET pending

We are looking for a Senior Software Engineer in Test for our Infinia Storage engineering team who will design, build and deliver strategic and modern components of the Quality Engineering process and…

Status: completed Created: 2026-05-27T16:09:50.340655Z Updated: 2026-05-27T16:11:38.223980Z API 3 duration: 53203 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

SDET

domain · Testing & Quality CASE DOMAIN

slug: sdet · id: 66 · source: db

Domain=Testing & Quality; The JD centers on software engineering for test automation, QE infrastructure, and test strategy in a storage systems context, which best matches SDET over pure automation or manual testing roles.

Matched skills

pythonpytestbashansibleQE methodologyfunctional testingstructural testingtest automationcode reviews

Matched dimensions

Quality EngineeringTest Automation InfrastructureTest Planning and DesignEngineering Velocity ImprovementDistributed Systems TestingCross-team Collaboration

Matched KRAs

design, build and deliver strategic and modern componentsdevelop software automation tools and infrastructureenable repeatable and extensible test and customer-focused simulated scenariosevaluate, recommend, and implement methods to expedite testing cyclesDrive design discussions, build prototypesConduct code reviews and improve scalability, stability and reliability of testDesign test plans, and test casesReview acceptance criteria, reviews test cases and test automation codeset up environments, and communicates regularly to project team on defectsCoordinate testing effort with other project teams across the globe

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
2
Skipped

Job description

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

 "DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC

 “The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA

DDN is the global leader in AI and multi-cloud data management at scale. Our cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence.

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management.

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage.

Job Description

We are looking for a Senior Software Engineer in Test for our Infinia Storage engineering team who will design, build and deliver strategic and modern components of the Quality Engineering process and infrastructure, for the Infinia engineering organization. This crucial member of QE will rely on their software engineering skills to develop software automation tools and infrastructure to enable repeatable and extensible test and customer-focused simulated scenarios, for all phases of testing data storage/intelligence subsystems. They will evaluate, recommend, and implement methods to expedite testing cycles and improve overall test and product quality.

• Drive design discussions, build prototypes and contribute to delivering high quality Test and Engineering Velocity solutions 
• Conduct code reviews and improve scalability, stability and reliability of test 
• Collaborate with teammates as a unified group of passionate engineers in an outcome- oriented environment. 
• Design test plans, and test cases, leveraging test automation 
• Review acceptance criteria, reviews test cases and test automation code, sets up environments, and communicates regularly to project team on defects, issues, and QE status 
• Coordinate testing effort with other project teams across the globe 
• Work closely with the Test Architect, Test Leads, Test Engineers and Developers/Designers to understand and provide solutions for any challenges that could impact the delivery of test automation. 
• Participation in a team on-call rotation providing seven-day week out of hours coverage, including the provision of after-hours and weekend support work when required.


 Qualifications:

• BS/MS/Ph.D in Computer Science, Computer Engineering, Statistics, Mathematics or equivalent degree/experience. 
• 6+ years of Software Development or Software Development for Test experience, preferably in technology domains involving distributed concurrent systems, data or storage systems. 
• Experience with QE methodology, functional and structural testing techniques (Agile a plus) 
• Must have experience in python or related modern high-level languages, pytest and bash. Experience in ansible is a plus. 
• Good problem solving, organizational, interpersonal and team skills 
• Ability to work seamlessly as part of a multi-site, multicultural engineering team 
• Self-motivated, passionate, and driven to achieve committed milestones 
• Strong team player with excellent written and verbal skills 
• Ability to work in a fast-paced development environment with a broad scope of evolving responsibilities


Preferred Experience

• Ability to read and understand coding languages and logic including C++ and GoLang 
• Knowledge of parallel file system solutions (Lustre, GPFS), NVM storage technology or distributed key-value storage systems 
• Knowledge of Object Storage and its usage 
• High Performance Computing system installation and management is helpful to perform day-to-day activities for this role


This position requires participation in an on-call rotation to provide after-hours support as needed.

 DDN

Our team is highly motivated and focused on engineering excellence.

We look for individuals who appreciate challenging themselves and thrive on curiosity.

Engineers are encouraged to work across multiple areas of the company.

We operate with a flat organizational structure.

All employees are expected to be hands-on and to contribute directly to the company’s mission.

Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important.

All engineers and researchers are expected to have strong communication skills.

They should be able to concisely and accurately share knowledge with their teammates.

Interview Process

After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 30-minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:

• Coding assessment in a language of your choice. 
• Systems design: Translate high-level requirements into a scalable, fault-tolerant service. 
• Systems hands-on: Demonstrate practical skills in a live problem-solving session. 
• Project deep-dive: Present your past exceptional work to a small audience. 
• Meet and greet with the wider team. 
• Our goal is to finish the main process within one week. 
• We don’t rely on recruiters for assessments. 
• Every application is reviewed by a member of our technical team.


DataDirect Networks, Inc. is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, transgender, sex stereotyping, sexual orientation, national origin, disability, protected Veteran Status, or any other characteristic protected by applicable federal, state, or local law.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
pytest Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: pytest id=2370 · pytest

Aliases — catalog

  • pytest (CANONICAL) primary

Context tags (catalog)

assert command line options coverage report fixture mock parameterized tests plugins pytest-bdd pytest-cov pytest-xdist test discovery test runner test suite tox unittest

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Testing Tool
Vendor
pytest-dev
License
mit
Year introduced
2014
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Pytest appears in many Python job descriptions and is a standard testing tool in the Python ecosystem, with broad GitHub usage and active maintenance.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
513
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Testing and Quality Assurance Catalog dimension db id 12

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Testing and Quality Assurance
testing-and-quality-assurance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Bash Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Bash id=103 · bash

Aliases — catalog

  • Bash (VERSION)
  • Bash 3.x (VERSION)
  • Bash 4.x (VERSION)
  • Bash 5.x (VERSION)
  • GNU Bash (VERSION)
  • bash (VERSION)
  • bash 3 (VERSION)
  • bash 3.x (VERSION)
  • bash 4 (VERSION)
  • bash 4.x (VERSION)
  • bash 5 (VERSION)
  • bash 5.x (VERSION)

Context tags (catalog)

Linux POSIX Unix alias awk chmod cron environment variables grep here-doc pipes sed shebang shell scripting ssh stdin stdout xargs

Stored enrichment (catalog DB)

Category
Language
Sub-category
Shell Language
Vendor
GNU Project
License
gpl_v3
Year introduced
1989
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
5.x

Maturity reasoning: Bash appears in many DevOps, SRE, and Linux admin job descriptions and remains the default shell on most Unix-like systems, with no vendor sunset or clear replacement in mainstream hiring.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
238
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Ansible Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Ansible id=721 · ansible

Aliases — catalog

  • Ansible (CANONICAL) primary

Context tags (catalog)

AWX Ansible Tower CI/CD Jinja2 SSH YAML ad-hoc commands agentless ansible-galaxy ansible-vault automation collections configuration drift deployment facts handlers idempotency idempotent inventory modules orchestration playbook playbooks roles task templates

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Configuration Management Tool
Vendor
Red Hat
License
apache_2
Year introduced
2012
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Commonly listed in DevOps/SRE job descriptions for config management and automation; strong GitHub usage and Red Hat/AWX ecosystem signal broad adoption.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
576
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Configuration Management Catalog dimension db id 133

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Configuration Management
configuration-management
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: C# id=4 · c

Aliases — catalog

  • C# (CANONICAL) primary
  • C (CANONICAL)
  • C# 1 (VERSION)
  • C# 10 (VERSION)
  • C# 11 (VERSION)
  • C# 12 (VERSION)
  • C# 13 (VERSION)
  • C# 14 (VERSION)
  • C# 2 (VERSION)
  • C# 3 (VERSION)
  • C# 4 (VERSION)
  • C# 5 (VERSION)
  • C# 6 (VERSION)
  • C# 7 (VERSION)
  • C# 8 (VERSION)
  • C# 9 (VERSION)
  • C# latest (VERSION)
  • C#1 (VERSION)
  • C#10 (VERSION)
  • C#11 (VERSION)
  • C#12 (VERSION)
  • C#2 (VERSION)
  • C#3 (VERSION)
  • C#4 (VERSION)
  • C#5 (VERSION)
  • C#6 (VERSION)
  • C#7 (VERSION)
  • C#8 (VERSION)
  • C#9 (VERSION)
  • C++ (CANONICAL)
  • C++03 (VERSION)
  • C++11 (VERSION)
  • C++14 (VERSION)
  • C++17 (VERSION)
  • C++20 (VERSION)
  • C++23 (VERSION)
  • C++26 (VERSION)
  • C++98 (VERSION)
  • c sharp (VERSION)
  • c# (VERSION)
  • cpp03 (VERSION)
  • cpp11 (VERSION)
  • cpp14 (VERSION)
  • cpp17 (VERSION)
  • cpp20 (VERSION)
  • cpp23 (VERSION)
  • cpp26 (VERSION)
  • cpp98 (VERSION)
  • csharp (VERSION)
  • modern C++ (VERSION)

Context tags (catalog)

.NET ASP.NET Azure Boost C# 9 C11 C99 CLR CMake Entity Framework LINQ MSBuild MVC Makefile NuGet Qt RAII Roslyn STL TDD Unity Visual Studio WPF Web API WinForms Xamarin async/await attributes buffer overflow constexpr delegates dependency injection dynamic memory events free function pointer gcc gdb header files inline interfaces linker malloc memory leak memory management move semantics multithreading operator overloading pointer pointers preprocessor segmentation fault smart pointers stdio.h stdlib.h struct syntax error templates typedef xUnit

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Microsoft
License
mit
Year introduced
2000
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
latest

Maturity reasoning: C# is a mainstream hiring staple with high JD volume across .NET, Azure, and enterprise roles; Microsoft continues active platform investment in .NET, reinforcing broad adoption.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • C# and .NET Languages Catalog dimension db id 362

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer

  • Cross-Platform App Languages Catalog dimension db id 167

    Library dimension (catalog)

    Roles linked in library: Hybrid Mobile Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Sitecore Development Languages Catalog dimension db id 438

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

  • Video Codec Languages and DSLs Catalog dimension db id 225

    Library dimension (catalog)

    Roles linked in library: Video Codec Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
C# and .NET Languages
c-and-net-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sitecore Development Languages
sitecore-development-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Video Codec Languages and DSLs
video-codec-languages-and-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Go id=3 · go

Aliases — catalog

  • Go (CANONICAL) primary
  • Go 1.0 (VERSION)
  • Go 1.1 (VERSION)
  • Go 1.10 (VERSION)
  • Go 1.11 (VERSION)
  • Go 1.12 (VERSION)
  • Go 1.13 (VERSION)
  • Go 1.14 (VERSION)
  • Go 1.15 (VERSION)
  • Go 1.16 (VERSION)
  • Go 1.17 (VERSION)
  • Go 1.18 (VERSION)
  • Go 1.19 (VERSION)
  • Go 1.2 (VERSION)
  • Go 1.20 (VERSION)
  • Go 1.21 (VERSION)
  • Go 1.22 (VERSION)
  • Go 1.3 (VERSION)
  • Go 1.4 (VERSION)
  • Go 1.5 (VERSION)
  • Go 1.6 (VERSION)
  • Go 1.7 (VERSION)
  • Go 1.8 (VERSION)
  • Go 1.9 (VERSION)
  • Go 1.x (VERSION)
  • Golang (VERSION)
  • go 1.18 (VERSION)
  • go 1.19 (VERSION)
  • go 1.20 (VERSION)
  • go 1.21 (VERSION)
  • go 1.22 (VERSION)
  • go latest (VERSION)
  • go1.18 (VERSION)
  • go1.19 (VERSION)
  • go1.20 (VERSION)
  • go1.21 (VERSION)
  • go1.22 (VERSION)
  • go1.x (VERSION)
  • golang (VERSION)

Context tags (catalog)

Beego Channel Concurrency Context Docker Echo Gin Go modules Golang Goroutine HTTP HTTP server Interface JSON JSON encoding Kubernetes Microservices REST API Struct Testing channels concurrency context package context.Context error handling gRPC goroutines interfaces microservices middleware modules net/http protobuf structs testing

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Google
License
bsd
Year introduced
2009
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Go appears in many current job descriptions for backend, cloud, and DevOps roles, and is a standard language in Kubernetes, Docker, and cloud-native stacks; strong GitHub and ecosystem adoption signal broad market demand.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Go Language and Toolchain Catalog dimension db id 367

    Library dimension (catalog)

    Roles linked in library: Go Backend Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go Language and Toolchain
go-language-and-toolchain
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Functional Testing Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Integration testing id=56 · integration-testing

Aliases — catalog

  • Integration testing (CANONICAL) primary
  • integration testing (CANONICAL)

Context tags (catalog)

API testing CI/CD Cucumber JUnit Selenium behavior-driven development continuous integration contract testing end-to-end end-to-end testing fixtures mocking pytest quality assurance regression testing smoke testing stubs system testing test automation test cases test coverage test data test frameworks test harness test strategy test suite test-driven development

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Testing Methodology
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Integration testing is a standard QA skill in job descriptions across backend, frontend, and DevOps roles; it’s commonly paired with CI/CD and tools like Jest, Cypress, and Testcontainers.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
44
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Testing and Defect Resolution Catalog dimension db id 262

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Testing and Quality Assurance Catalog dimension db id 12

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Testing and Defect Resolution
testing-and-defect-resolution
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Testing and Quality Assurance
testing-and-quality-assurance
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Structural Testing Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Testing Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Test Automation Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Testing Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Code Review Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Code Review id=516 · code-review

Aliases — catalog

  • Code Review (CANONICAL)

Context tags (catalog)

Bitbucket GitHub GitLab PR review approval workflow branch protection code quality diff inline comments linting merge request pair programming pull request review checklist static analysis

Stored enrichment (catalog DB)

Category
SoftSkill
Sub-category
Code Review
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Code review is a standard hiring-pipeline requirement in engineering JDs and is built into major platforms like GitHub/GitLab pull-request workflows, indicating broad adoption.

Skill profile (library / DB)

Skill nature
PRACTICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
58
Sub-category id
364
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Distributed Systems Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Distributed Systems id=1369 · distributed-systems

Aliases — catalog

  • Distributed Systems (CANONICAL)

Context tags (catalog)

CAP theorem Docker Swarm Kafka MapReduce Zookeeper consensus algorithms distributed databases eventual consistency fault tolerance gRPC load balancing message queues microservices replication sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Distributed Systems
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common hiring requirement in backend/platform JDs at large tech firms; appears across AWS, Kafka, microservices, and systems roles, with strong GitHub/Stack Overflow activity and no sunset signal.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1035
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Performance and Scalability Tuning Catalog dimension db id 11

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Concurrent Systems Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Lustre Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
File Systems
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
GPFS Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
File Systems
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
NVM Storage Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Storage Solutions
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Distributed Key-Value Storage Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Object Storage Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Storage Solutions
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
High Performance Computing Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
pytest in_db
Testing and Quality Assurance
testing-and-quality-assurance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Bash in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Bash in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Ansible in_db
Configuration Management
configuration-management
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
C# and .NET Languages
c-and-net-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Sitecore Development Languages
sitecore-development-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C++ in_db
Video Codec Languages and DSLs
video-codec-languages-and-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go in_db
Go Language and Toolchain
go-language-and-toolchain
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Go in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Functional Testing new
Testing and Defect Resolution
testing-and-defect-resolution
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Functional Testing new
Testing and Quality Assurance
testing-and-quality-assurance
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Code Review in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Distributed Systems in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Distributed Systems in_db
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Distributed Systems in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Structural Testing | type=Testing Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Test Automation | type=Testing Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Concurrent Systems | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Lustre | type=File Systems subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed GPFS | type=File Systems subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed NVM Storage | type=Storage Solutions subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Distributed Key-Value Storage | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Object Storage | type=Storage Solutions subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed High Performance Computing | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
dimension_skill_link_proposed Functional Testing ↔ Testing and Defect Resolution
dimension_skill_link_proposed Functional Testing ↔ Testing and Quality Assurance
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Software Engineer in Test
CompanyDataDirect Networks
Experience6+ years of Software Development or Software Development for Test experience
DomainIT Services & Consulting
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "This is an incredible opportunity",
      "last_5_words": "research and manufacturing."
    },
    "text": "This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world\u0027s most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.",
    "word_count": 64
  },
  "certifications": [],
  "company_name": "DataDirect Networks",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "Tech Consulting",
        "Software Development"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC - Computer Science (or related)",
      "raw": "BS/MS/Ph.D in Computer Science, Computer Engineering, Statistics, Mathematics or equivalent degree/experience.",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 6,
    "raw": "6+ years of Software Development or Software Development for Test experience"
  },
  "job_locations": [],
  "role": "Senior Software Engineer in Test",
  "role_aliases": [
    "Software Engineer in Test",
    "QA Engineer",
    "Test Engineer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Job Description",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "We are looking for a",
        "last_5_words": "test and product quality."
      },
      "text": "We are looking for a Senior Software Engineer in Test for our Infinia Storage engineering team who will design, build and deliver strategic and modern components of the Quality Engineering process and infrastructure, for the Infinia engineering organization. This crucial member of QE will rely on their software engineering skills to develop software automation tools and infrastructure to enable repeatable and extensible test and customer-focused simulated scenarios, for all phases of testing data storage/intelligence subsystems. They will evaluate, recommend, and implement methods to expedite testing cycles and improve overall test and product quality.",
      "word_count": 90
    },
    {
      "bullet_count": 8,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Drive design discussions, build",
        "last_5_words": "after-hours and weekend support work when required."
      },
      "text": "\u2022 Drive design discussions, build prototypes and contribute to delivering high quality Test and Engineering Velocity solutions \n\u2022 Conduct code reviews and improve scalability, stability and reliability of test \n\u2022 Collaborate with teammates as a unified group of passionate engineers in an outcome- oriented environment. \n\u2022 Design test plans, and test cases, leveraging test automation \n\u2022 Review acceptance criteria, reviews test cases and test automation code, sets up environments, and communicates regularly to project team on defects, issues, and QE status \n\u2022 Coordinate testing effort with other project teams across the globe \n\u2022 Work closely with the Test Architect, Test Leads, Test Engineers and Developers/Designers to understand and provide solutions for any challenges that could impact the delivery of test automation. \n\u2022 Participation in a team on-call rotation providing seven-day week out of hours coverage, including the provision of after-hours and weekend support work when required.",
      "word_count": 139
    },
    {
      "bullet_count": 9,
      "heading": "Qualifications",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 BS/MS/Ph.D in Computer Science,",
        "last_5_words": "scope of evolving responsibilities"
      },
      "text": "\u2022 BS/MS/Ph.D in Computer Science, Computer Engineering, Statistics, Mathematics or equivalent degree/experience. \n\u2022 6+ years of Software Development or Software Development for Test experience, preferably in technology domains involving distributed concurrent systems, data or storage systems. \n\u2022 Experience with QE methodology, functional and structural testing techniques (Agile a plus) \n\u2022 Must have experience in python or related modern high-level languages, pytest and bash. Experience in ansible is a plus. \n\u2022 Good problem solving, organizational, interpersonal and team skills \n\u2022 Ability to work seamlessly as part of a multi-site, multicultural engineering team \n\u2022 Self-motivated, passionate, and driven to achieve committed milestones \n\u2022 Strong team player with excellent written and verbal skills \n\u2022 Ability to work in a fast-paced development environment with a broad scope of evolving responsibilities",
      "word_count": 139
    },
    {
      "bullet_count": 4,
      "heading": "Preferred Experience",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Ability to read and understand",
        "last_5_words": "activities for this role"
      },
      "text": "\u2022 Ability to read and understand coding languages and logic including C++ and GoLang \n\u2022 Knowledge of parallel file system solutions (Lustre, GPFS), NVM storage technology or distributed key-value storage systems \n\u2022 Knowledge of Object Storage and its usage \n\u2022 High Performance Computing system installation and management is helpful to perform day-to-day activities for this role",
      "word_count": 56
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "pytest"
    },
    {
      "is_primary": true,
      "skill_name": "Bash"
    },
    {
      "is_primary": false,
      "skill_name": "Ansible"
    },
    {
      "is_primary": false,
      "skill_name": "C++"
    },
    {
      "is_primary": false,
      "skill_name": "Go"
    },
    {
      "is_primary": false,
      "skill_name": "Agile"
    },
    {
      "is_primary": true,
      "skill_name": "Functional Testing"
    },
    {
      "is_primary": true,
      "skill_name": "Structural Testing"
    },
    {
      "is_primary": true,
      "skill_name": "Test Automation"
    },
    {
      "is_primary": true,
      "skill_name": "Code Review"
    },
    {
      "is_primary": false,
      "skill_name": "Distributed Systems"
    },
    {
      "is_primary": false,
      "skill_name": "Concurrent Systems"
    },
    {
      "is_primary": false,
      "skill_name": "Lustre"
    },
    {
      "is_primary": false,
      "skill_name": "GPFS"
    },
    {
      "is_primary": false,
      "skill_name": "NVM Storage"
    },
    {
      "is_primary": false,
      "skill_name": "Distributed Key-Value Storage"
    },
    {
      "is_primary": false,
      "skill_name": "Object Storage"
    },
    {
      "is_primary": false,
      "skill_name": "High Performance Computing"
    }
  ],
  "jd_role": {
    "display_name": "Senior Software Engineer in Test",
    "rationale": null,
    "role_aliases": [
      "Software Engineer in Test",
      "QA Engineer",
      "Test Engineer"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "This is an incredible opportunity",
        "last_5_words": "research and manufacturing."
      },
      "text": "This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. DataDirect Networks (DDN) is a global market leader renowned for powering many of the world\u0027s most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.",
      "word_count": 64
    },
    "certifications": [],
    "company_name": "DataDirect Networks",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Tech Consulting",
          "Software Development"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE/BSC - Computer Science (or related)",
        "raw": "BS/MS/Ph.D in Computer Science, Computer Engineering, Statistics, Mathematics or equivalent degree/experience.",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": null,
      "min": 6,
      "raw": "6+ years of Software Development or Software Development for Test experience"
    },
    "job_locations": [],
    "role": "Senior Software Engineer in Test",
    "role_aliases": [
      "Software Engineer in Test",
      "QA Engineer",
      "Test Engineer"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Job Description",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "We are looking for a",
          "last_5_words": "test and product quality."
        },
        "text": "We are looking for a Senior Software Engineer in Test for our Infinia Storage engineering team who will design, build and deliver strategic and modern components of the Quality Engineering process and infrastructure, for the Infinia engineering organization. This crucial member of QE will rely on their software engineering skills to develop software automation tools and infrastructure to enable repeatable and extensible test and customer-focused simulated scenarios, for all phases of testing data storage/intelligence subsystems. They will evaluate, recommend, and implement methods to expedite testing cycles and improve overall test and product quality.",
        "word_count": 90
      },
      {
        "bullet_count": 8,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Drive design discussions, build",
          "last_5_words": "after-hours and weekend support work when required."
        },
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API 2 — extract-details
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            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Scala Backend Developer",
              "id": 87,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "scala-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Performance and Scalability Tuning",
            "id": 11,
            "rationale": "Techniques for improving throughput, latency, and resource efficiency in PHP backend services. This includes profiling, query optimization, concurrency limits, memory use, and bottleneck analysis.",
            "slug": "performance-and-scalability-tuning",
            "source": "db"
          },
          "input_skill": "Distributed Systems",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "PHP Backend Developer",
              "id": 86,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "php-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Distributed Systems",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Distributed Systems",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Concurrent Systems",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concepts",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "concurrent-systems",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Lustre",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "File Systems",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "lustre",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "GPFS",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "File Systems",
          "skill_nature": "TOOL",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "gpfs",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "NVM Storage",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Storage Solutions",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "nvm-storage",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Distributed Key-Value Storage",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Databases",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "distributed-key-value-storage",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Object Storage",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Storage Solutions",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "object-storage",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "High Performance Computing",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Concepts",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "high-performance-computing",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Structural Testing",
    "Test Automation",
    "Concurrent Systems",
    "Lustre",
    "GPFS",
    "NVM Storage",
    "Distributed Key-Value Storage",
    "Object Storage",
    "High Performance Computing"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "SDET",
    "id": 66,
    "rationale": "Domain=Testing \u0026 Quality; The JD centers on software engineering for test automation, QE infrastructure, and test strategy in a storage systems context, which best matches SDET over pure automation or manual testing roles.",
    "role_archetype": null,
    "slug": "sdet",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "pytest",
      "tag": "in_db"
    },
    {
      "skill": "Bash",
      "tag": "in_db"
    },
    {
      "skill": "Ansible",
      "tag": "in_db"
    },
    {
      "skill": "C++",
      "tag": "in_db"
    },
    {
      "skill": "Go",
      "tag": "in_db"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    },
    {
      "skill": "Functional Testing",
      "tag": "in_db"
    },
    {
      "skill": "Structural Testing",
      "tag": "new"
    },
    {
      "skill": "Test Automation",
      "tag": "new"
    },
    {
      "skill": "Code Review",
      "tag": "in_db"
    },
    {
      "skill": "Distributed Systems",
      "tag": "in_db"
    },
    {
      "skill": "Concurrent Systems",
      "tag": "new"
    },
    {
      "skill": "Lustre",
      "tag": "new"
    },
    {
      "skill": "GPFS",
      "tag": "new"
    },
    {
      "skill": "NVM Storage",
      "tag": "new"
    },
    {
      "skill": "Distributed Key-Value Storage",
      "tag": "new"
    },
    {
      "skill": "Object Storage",
      "tag": "new"
    },
    {
      "skill": "High Performance Computing",
      "tag": "new"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 66,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Testing and Quality Assurance",
          "id": 12,
          "rationale": "Backend-specific test strategies used to validate service behavior and integration points. Covers automated test layers, contract checks, fixtures, and regression prevention.",
          "slug": "testing-and-quality-assurance",
          "source": "db"
        },
        "dimension_id": 12,
        "input_skill": "pytest",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
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          "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
          "slug": "cross-platform-app-languages",
          "source": "db"
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            "display_name": "Hybrid Mobile Developer",
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        "roles_from_db": [
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          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [],
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        "skill_tag": "in_db",
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          "display_name": "Sitecore Development Languages",
          "id": 438,
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          "source": "db"
        },
        "dimension_id": 438,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Sitecore Dev",
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            "rationale": null,
            "role_archetype": "Engineering",
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        ],
        "skill_dimension_saved": true,
        "skill_id": 4,
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          "rationale": "Implementation languages and codec-specific description languages used to build compression, decoding, and transform logic. This is the primary coding surface for codec behavior and bitstream manipulation.",
          "slug": "video-codec-languages-and-dsls",
          "source": "db"
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        "dimension_id": 225,
        "input_skill": "C++",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Video Codec Engineer",
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            "rationale": null,
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        "skill_id": 4,
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          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
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          "source": "db"
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        "dimension_id": 367,
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Go Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
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        "skill_dimension_saved": true,
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        "skipped_reason": null
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          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
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          "source": "db"
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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          "slug": "d_init_01",
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        "skill_id": 520,
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        "skill_dimension_saved": true,
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          "rationale": "Validates Pega rules, flows, and integrations and then troubleshoots defects found in lower environments or production. This is a coherent cluster because the role is expected to verify platform behavior and fix rule-level issues.",
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        "dimension_id": 262,
        "input_skill": "Functional Testing",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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            "display_name": "Pega Developer",
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            "slug": "pega-developer",
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        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
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          "difficulty_hint": "well_known",
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          "rationale": "Backend-specific test strategies used to validate service behavior and integration points. Covers automated test layers, contract checks, fixtures, and regression prevention.",
          "slug": "testing-and-quality-assurance",
          "source": "db"
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        "dimension_id": 12,
        "input_skill": "Functional Testing",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
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            "display_name": ".NET Backend Developer",
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            "role_archetype": "Engineering",
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            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
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          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
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