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Pipeline run

6251654b-768f-42be-b38a-7aad00d382de

Pipeline LLM cost (USD)
API 1: $0.0110 API 2: $0.0003 API 3: $0.0000 Total: $0.0114

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Cloud / Big Data Engineering
Design and run cloud/big data systems, automate deployments, and keep services secure, available, performant, and cost-controlled. Also troubleshoot incidents, lead RCAs, and improve platform scaling and developer productivity.
"Develop software and provide hands-on technical expertise to design, deploy, and optimize Cloud services and/or Big Data."
Tech stack maturity
Mainstream Modern
The skill set centers on established cloud and DevOps tooling plus widely adopted distributed data platforms, which aligns with a mainstream modern stack rather than bleeding-edge or legacy technology.
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): guardrails
Evidence — skills matched in JD (16)
Cloud Big Data Security Availability Performance Jenkins Ansible Spinnaker RCA Resilient Systems Spark Hadoop Kafka Cassandra DevOps SRE
Skill cluster (6 dimension groups, role-scoped)
Asynchronous Messaging and Event Streaming
Kafka
CI/CD Pipeline Platforms
Jenkins
Cloud Platforms
Cloud
Configuration Management
Ansible
Infrastructure as Code
DevOps
Cross-cutting / unaligned
Big Data Security Availability Performance Spinnaker RCA Resilient Systems Spark Hadoop Cassandra SRE
Show KRA description ↓
Develop software and provide hands-on technical expertise to design, deploy, and optimize Cloud services and/or Big Data. Improve the Security, Availability and Performance of the systems you build while managing Cloud Costs and maintain Compliance guardrails. Build automation using industry tools (like Jenkins, Ansible, Spinnaker, etc) to deploy hundreds of different services. Participate in On-Call and identify issues and drive them to resolution and conduct blameless RCA. Be the advocate to guide development team to build reliable and resilient service. Evangelize and contribute to best practices in library usage and end-to-end architecture. Design, develop, and maintain the Citrix Analytics platform. Extend the Citrix Analytics platform by researching and applying new big data technologies and stacks to solve business problems. Maintain the Citrix analytics platform by diagnosing, predicting, and correcting scaling problems. Work with large streams of data and technologies like Spark, Hadoop, Kafka, and Cassandra. Contribute to our team’s growing set of development platforms, tools, and processes. Build automation and tools that will increase the productivity of teams located in different GEOs. Provide input and feedback to teams regarding decisions surrounding topics such as infrastructure, data architectures, and DevOps/SRE strategy. Support and provide guidance to the company’s software engineering processes and standards.

Signals

Skill data-engineer
0.25
Alias devops-engineer
1.00
KRA cloud-architect
0.60

Post-classification

Centroidupdated · n=83
Alias collision log
New-role queue
New skills captured8
New KRA captured

Captured for admin review

Big Data primary DevOps Engineer pending
Security primary DevOps Engineer pending
Availability primary DevOps Engineer pending
Performance primary DevOps Engineer pending
Spinnaker primary DevOps Engineer pending
RCA primary DevOps Engineer pending
Resilient Systems primary DevOps Engineer pending
SRE primary DevOps Engineer pending
Status: completed Created: 2026-05-27T15:52:45.002543Z Updated: 2026-06-12T15:49:28.978753Z API 3 duration: 45562 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

DevOps Engineer

DevOps Tooling Developer

sub-role · 0.81 domain · DevOps & Platform CASE DOMAIN

slug: devops-engineer · id: 10 · source: db · sub-role slug: devops-tooling-developer

Domain=DevOps & Platform → sub-role devops-tooling-developer; The JD centers on cloud services, Big Data platforms, deployment automation, on-call incident response, reliability, and DevOps/SRE practices, which best matches DevOps Engineer over the narrower SRE or platform roles.

Matched skills

Cloud servicesBig DataJenkinsAnsibleSpinnakerOn-Callblameless RCACitrix Analytics platformSparkHadoopKafkaCassandra

Matched dimensions

Cloud and big data engineeringDeployment automationSite reliability and incident responseService reliability and resiliencePlatform engineering and developer productivityCloud cost management and complianceDistributed data systems

Matched KRAs

design, deploy, and optimize Cloud services and/or Big DataImprove the Security, Availability and Performancemanage Cloud Costs and maintain Compliance guardrailsBuild automation using industry toolsdeploy hundreds of different servicesParticipate in On-Call and identify issuesdrive them to resolution and conduct blameless RCADesign, develop, and maintain the Citrix Analytics platformdiagnosing, predicting, and correcting scaling problemsBuild automation and tools that will increase productivity

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
0
Skipped

Job description

Job Description
Citrix is rapidly developing and expanding its portfolio of large-scale cloud applications across all product lines, including app/desktop virtualization, networking, and content collaboration. These applications must deliver enterprise-grade performance, reliability, and integration while leveraging consumer internet economies of scale in multiple clouds (and in hybrid scenarios that reach behind the enterprise firewall). This requires excellent architecture and a dev-ops mindset in software development, operations, and site reliability engineering.
You should have a minimum of 3 years designing, developing, troubleshooting, and debugging complex software applications, as well as, experience demonstrating for others how to resolve issues in innovative and practical ways. You will work on a team of talented engineers responsible for designing, developing, optimizing, and extending the Citrix Analytics big data platform.
Role Responsibilities:


Develop software and provide hands-on technical expertise to design, deploy, and optimize Cloud services and/or Big Data.Improve the Security, Availability and Performance of the systems you build while managing Cloud Costs and maintain Compliance guardrails.Build automation using industry tools (like Jenkins, Ansible, Spinnaker, etc) to deploy hundreds of different services.Participate in On-Call and identify issues and drive them to resolution and conduct blameless RCA.Be the advocate to guide development team to build reliable and resilient service.Evangelize and contribute to best practices in library usage and end-to-end architecture.Design, develop, and maintain the Citrix Analytics platform.Extend the Citrix Analytics platform by researching and applying new big data technologies and stacks to solve business problems.Maintain the Citrix analytics platform by diagnosing, predicting, and correcting scaling problems.Work with large streams of data and technologies like Spark, Hadoop, Kafka, and Cassandra.Contribute to our team’s growing set of development platforms, tools, and processes.Build automation and tools that will increase the productivity of teams located in different GEOs.Provide input and feedback to teams regarding decisions surrounding topics such as infrastructure, data architectures, and DevOps/SRE strategy.Support and provide guidance to the company’s software engineering processes and standards.Basic Qualifications:


3-5 years’ experience with managing and deploying a cloud infrastructure at scale within a public cloud environment.3-5 years’ experience managing deployments with Infrastructure as code and Immutable infrastructure.Experience in converting toil to automated jobs and identify recurring incidents using trend analysis.Experience with at least one of the major cloud providers including Azure, AWS, or GCP.Have experience writing applications using C#, Python, or JavaScript.Scripting in PowerShell/Bash.Requires deep knowledge of job area obtained through advanced education combined with experience.Good understanding of TCP/IP and networking fundamentals.Experienced in code review and architecture review.Experience with logging platforms and application performance metrics a plus - New Relic, Splunk, Application Insights.Candidate should be a graduate BE or equivalent to Engineering degree.Preferred Qualifications:
Experience with container technologies: Kubernetes, Docker.3 years plus of experience building Cloud services and distributed systems – deployment, monitoring, scaling, debugging is desirable.Azure or AWS certifications.Strong CS fundamentals, with good demonstrated experience of working on big data and troubleshooting problems and driving them to resolution.Experience with Python, Java, or Scala programming language.2 years of experience designing and implementing data ingestion and transformation for big data platforms. (Spark, Hadoop, Kafka, etc.). Proven track record designing highly parallelized data ingestion and transformation jobs in Spark including Spark Streaming. Production experience working and troubleshooting with Apache Spark clusters.

Skills from this JD

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

Cloud Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Cloud id=1572 · cloud

Aliases — catalog

  • Cloud (CANONICAL)

Context tags (catalog)

AWS Azure DevOps Docker Google Cloud IaaS Kubernetes PaaS SaaS cloud migration cloud security hybrid cloud microservices multi-cloud serverless

Stored enrichment (catalog DB)

Category
Domain
Sub-category
Cloud Computing
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Cloud is a hiring-pipeline staple: AWS, Azure, and GCP appear in a large share of modern infrastructure JDs, and major vendors continue expanding cloud services rather than sunsetting them.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
37
Sub-category id
1177
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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Big Data 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Security 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Availability 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Performance 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Jenkins Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Jenkins id=283 · jenkins

Aliases — catalog

  • Jenkins (CANONICAL) primary

Context tags (catalog)

Blue Ocean CI/CD Declarative Pipeline Docker Groovy Jenkinsfile Kubernetes agents artifact repository artifacts automation build triggers integration multibranch pipeline pipeline plugins shared libraries stages test automation version control webhooks

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Ci Cd Tool
Vendor
CloudBees
License
mit
Year introduced
2011
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Jenkins remains a common CI/CD requirement in job postings and enterprise DevOps stacks, with broad plugin ecosystem and long-running GitHub activity despite newer alternatives.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
184
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension saved
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Ansible Primary 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 saved
Spinnaker 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
DevOps Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RCA 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
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Resilient Systems 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Spark Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

  • Apache Spark (CANONICAL)
  • apache spark 3 (VERSION)
  • spark (VERSION)
  • spark 3 (VERSION)
  • spark 3.x (VERSION)
  • spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Distributed Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.94
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1021
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hadoop Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Hadoop id=1351 · hadoop

Aliases — catalog

  • Hadoop (CANONICAL)

Context tags (catalog)

Big Data Data Lake Distributed Computing ELT ETL Flume HDFS Hive Kafka MapReduce NoSQL Oozie Pig Spark Sqoop YARN

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2006
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Job postings still mention Hadoop for legacy big-data stacks, but JD volume has fallen as Spark and cloud warehouses replaced MapReduce-era clusters.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
91
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kafka id=36 · kafka

Aliases — catalog

  • Kafka (CANONICAL) primary

Context tags (catalog)

Apache Flink Apache Kafka Apache Pulsar Apache Spark Avro KSQL Kafka API Kafka Connect Kafka Streams ZooKeeper Zookeeper backpressure brokers consumer consumer group consumer groups event sourcing event-driven architecture exactly-once semantics fault tolerance high throughput log compaction message broker message queue microservices offsets partition partitioning partitions producer producer API real-time analytics real-time data replication schema registry stream processing topic topic partitioning topics

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Event Stream Store
Vendor
Confluent
License
apache_2
Year introduced
2011
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Kafka appears in many production JDs for event streaming and data pipelines, and remains a standard platform in cloud/vendor offerings (e.g., Confluent, AWS MSK), indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
3533
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Asynchronous Messaging and Event Streaming Catalog dimension db id 297

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer

  • Messaging and Background Jobs Catalog dimension db id 291

    Library dimension (catalog)

    Roles linked in library: PHP Backend Developer, Python Backend Developer, Ruby Backend Developer

  • Messaging and Event Streaming Catalog dimension db id 8

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cassandra Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Cassandra id=1354 · cassandra

Aliases — catalog

  • Cassandra (CANONICAL)

Context tags (catalog)

CQL Cluster Consistency DSE Data Modeling DataStax Eventual Consistency NoSQL Partitioning Replication ScyllaDB Spark Thrift TinkerPop Wide Column

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Wide Column Store
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2008
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Apache Cassandra appears in many production data-platform JDs and is a common choice for high-write, distributed workloads; GitHub and vendor docs show sustained activity rather than sunset signals.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
31
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DevOps Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: DevOps id=1216 · devops

Aliases — catalog

  • DevOps (CANONICAL)

Context tags (catalog)

Agile Ansible Automation CI/CD Cloud-native Continuous Deployment Continuous Integration Docker GitOps Infrastructure as Code Jenkins Kubernetes Microservices Monitoring SRE Terraform

Stored enrichment (catalog DB)

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

Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
922
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Deployment and Release Patterns Catalog dimension db id 140

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Infrastructure as Code Catalog dimension db id 132

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension saved
Deployment and Release Patterns
deployment-and-release-patterns
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension saved
SRE 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
Practices
Sub-category
general
Skill nature
PRACTICE
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
Cloud in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Jenkins in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension saved
Jenkins in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Ansible in_db
Configuration Management
configuration-management
Existing dimension (library) · Role↔dimension saved
Spark in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hadoop in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cassandra in_db
Cloud Storage and Data Services
cloud-storage-and-data-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DevOps in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension saved
DevOps in_db
Deployment and Release Patterns
deployment-and-release-patterns
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DevOps in_db
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension saved

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Big Data | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Security | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Availability | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Performance | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Spinnaker | type=DevOps Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed RCA | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Resilient Systems | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed SRE | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleSoftware Engineer
CompanyCitrix
Experience3-5 years’ experience with managing and deploying a cloud infrastructure at scale within a public cloud environment.
DomainIT Services & Consulting
JD type pass

Certifications

Azure or AWS certifications
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [
    "Azure or AWS certifications"
  ],
  "company_name": "Citrix",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "ITES",
        "BPO"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Engineering",
      "raw": "Candidate should be a graduate BE or equivalent to Engineering degree.",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 5,
    "min": 3,
    "raw": "3-5 years\u2019 experience with managing and deploying a cloud infrastructure at scale within a public cloud environment."
  },
  "job_locations": [],
  "role": "Software Engineer",
  "role_aliases": [
    "Software Developer",
    "Cloud Engineer",
    "DevOps Engineer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 12,
      "heading": "Role Responsibilities",
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  "urls": []
}
API 1 — extract-from-jd click to toggle
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}
API 2 — extract-details
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      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practices",
          "skill_nature": "PRACTICE",
          "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": "sre",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Big Data",
    "Security",
    "Availability",
    "Performance",
    "Spinnaker",
    "RCA",
    "Resilient Systems",
    "SRE"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "DevOps Engineer",
    "id": 10,
    "rationale": "Domain=DevOps \u0026 Platform \u2192 sub-role devops-tooling-developer; The JD centers on cloud services, Big Data platforms, deployment automation, on-call incident response, reliability, and DevOps/SRE practices, which best matches DevOps Engineer over the narrower SRE or platform roles.",
    "role_archetype": null,
    "slug": "devops-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Cloud",
      "tag": "in_db"
    },
    {
      "skill": "Big Data",
      "tag": "new"
    },
    {
      "skill": "Security",
      "tag": "new"
    },
    {
      "skill": "Availability",
      "tag": "new"
    },
    {
      "skill": "Performance",
      "tag": "new"
    },
    {
      "skill": "Jenkins",
      "tag": "in_db"
    },
    {
      "skill": "Ansible",
      "tag": "in_db"
    },
    {
      "skill": "Spinnaker",
      "tag": "new"
    },
    {
      "skill": "RCA",
      "tag": "new"
    },
    {
      "skill": "Resilient Systems",
      "tag": "new"
    },
    {
      "skill": "Spark",
      "tag": "in_db"
    },
    {
      "skill": "Hadoop",
      "tag": "in_db"
    },
    {
      "skill": "Kafka",
      "tag": "in_db"
    },
    {
      "skill": "Cassandra",
      "tag": "in_db"
    },
    {
      "skill": "DevOps",
      "tag": "in_db"
    },
    {
      "skill": "SRE",
      "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": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "Cloud",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "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": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "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"
          },
          {
            "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1572,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "Jenkins",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 283,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "Jenkins",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 283,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Configuration Management",
          "id": 133,
          "rationale": "Host and fleet configuration tools used to standardize operating system state, bootstrap servers, and enforce baseline settings. This is distinct from IaC because it focuses on in-guest configuration rather than cloud resource provisioning.",
          "slug": "configuration-management",
          "source": "db"
        },
        "dimension_id": 133,
        "input_skill": "Ansible",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 721,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Spark",
        "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": 1350,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Hadoop",
        "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": 1351,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Asynchronous Messaging and Event Streaming",
          "id": 297,
          "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
          "slug": "asynchronous-messaging-and-event-streaming",
          "source": "db"
        },
        "dimension_id": 297,
        "input_skill": "Kafka",
        "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": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Messaging and Background Jobs",
          "id": 291,
          "rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
          "slug": "messaging-and-background-jobs",
          "source": "db"
        },
        "dimension_id": 291,
        "input_skill": "Kafka",
        "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": "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"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Messaging and Event Streaming",
          "id": 8,
          "rationale": "Transport-layer systems used to move events and decouple producers from consumers. Data engineers use these systems to ingest, buffer, and distribute event data before downstream processing.",
          "slug": "messaging-and-event-streaming",
          "source": "db"
        },
        "dimension_id": 8,
        "input_skill": "Kafka",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Storage and Data Services",
          "id": 144,
          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
          "slug": "cloud-storage-and-data-services",
          "source": "db"
        },
        "dimension_id": 144,
        "input_skill": "Cassandra",
        "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 Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1354,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "DevOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1216,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment and Release Patterns",
          "id": 140,
          "rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
          "slug": "deployment-and-release-patterns",
          "source": "db"
        },
        "dimension_id": 140,
        "input_skill": "DevOps",
        "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 Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1216,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 10,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Infrastructure as Code",
          "id": 132,
          "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
          "slug": "infrastructure-as-code",
          "source": "db"
        },
        "dimension_id": 132,
        "input_skill": "DevOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1216,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "6251654b-768f-42be-b38a-7aad00d382de"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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