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Pipeline run

7252e427-a97a-432b-967e-3f3f869cd9a0

Pipeline LLM cost (USD)
API 1: $0.0096 API 2: $0.0008 API 3: $0.0000 Total: $0.0104

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Verification & Physical Design
Develop test benches and run/debug RTL, gate-level SDF, and mixed-signal simulations; perform physical verification/DRC on analog-mixed-signal IP, and support customers plus QA/documentation improvements.
"Perform RTL and gate-level SDF-annotated simulations and debug."
Tech stack maturity
Mainstream Modern cache hit
FPGA/ASIC engineering with Perl and Python is a specialized hardware workflow that commonly uses modern scripting and automation, but does not by itself imply cloud-native or bleeding-edge AI infrastructure.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 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):
Evidence — skills matched in JD (25)
Verilog Perl Python RTL SDF-annotated simulation Cadence Virtuoso Synopsys Custom Compiler Calibre Assura Physical verification Design rule checks EDA tools Synopsys FC Synopsys ICC2 PrimeTime Formality ICV Static timing analysis Synthesis DFT ATPG Tcl Mixed-signal simulation High-speed communication protocols Silicon bring-up
Skill cluster (2 dimension groups, role-scoped)
Python Programming
Python
Cross-cutting / unaligned
Verilog Perl RTL SDF-annotated simulation Cadence Virtuoso Synopsys Custom Compiler Calibre Assura Physical verification Design rule checks EDA tools Synopsys FC Synopsys ICC2 PrimeTime Formality ICV Static timing analysis Synthesis DFT ATPG Tcl Mixed-signal simulation High-speed communication protocols Silicon bring-up
Show KRA description ↓
• Generate test benches and test cases. • Perform RTL and gate-level SDF-annotated simulations and debug. • May perform mixed-signal (digital + analog) simulations and debug. • Interact with our application engineers and provide guidance to customers. • Participate in the generation of data books, application notes, and white papers. • Contribute to enhance quality assurance methodology by adding more quality checks/gatings. • Perform physical verification and design rule checks to ensure design integrity and manufacturability. • Enhance the quality and reliability of our PVT Sensor IPs. • Improve project forecasting and monitoring capabilities. • Support the development of innovative solutions for chip design and verification. • Strengthen customer relationships through effective guidance and support. • Contribute to knowledge sharing through documentation and training materials. • Drive continuous improvement in design methodologies and tools. • Bachelor’s or master’s degree in electrical engineering or a related field. • 3 to 7+ years of experience in A&MS frontend and backend views & collaterals development flows. • Proficiency in industry-standard EDA tools, such as Cadence Virtuoso or Synopsys Custom Compiler. • Exceptional knowledge of layout design methods, techniques, and methodologies. • Experience with physical verification tools, such as Calibre or Assura. • Understanding of semiconductor process technologies and their impact on layout design. We are seeking someone with excellent problem-solving and systematic skills, who can work effectively in a team-oriented environment. Familiarity with the Synopsys Tool set (such as FC/ICC2, Primetime, Formality, ICV) is essential. Good communication and interpersonal skills are a must. Experience in writing RTL Code, with solid Verilog, PERL, and Python skills, and TCL as an addition, will be highly valuable. Understanding of static timing analysis and synthesis, DFT/ATPG skills, and high-speed communication protocols are added advantages. Previous experience in customer support and/or silicon bring-up will be a plus.

Signals

Skill data-engineer
0.05
Alias
KRA devops-engineer
0.51

Post-classification

Centroidupdated · n=2
Alias collision log
New-role queue
New skills captured23
New KRA capturedyes

Captured for admin review

Verilog primary FPGA / ASIC Engineer pending
Tcl FPGA / ASIC Engineer pending
RTL primary FPGA / ASIC Engineer pending
SDF-annotated simulation primary FPGA / ASIC Engineer pending
Mixed-signal simulation FPGA / ASIC Engineer pending
Cadence Virtuoso primary FPGA / ASIC Engineer pending
Synopsys Custom Compiler primary FPGA / ASIC Engineer pending
Calibre primary FPGA / ASIC Engineer pending
Assura primary FPGA / ASIC Engineer pending
Physical verification primary FPGA / ASIC Engineer pending
Design rule checks primary FPGA / ASIC Engineer pending
EDA tools primary FPGA / ASIC Engineer pending
Synopsys FC primary FPGA / ASIC Engineer pending
Synopsys ICC2 primary FPGA / ASIC Engineer pending
PrimeTime primary FPGA / ASIC Engineer pending
Formality primary FPGA / ASIC Engineer pending
ICV primary FPGA / ASIC Engineer pending
Static timing analysis primary FPGA / ASIC Engineer pending
Synthesis primary FPGA / ASIC Engineer pending
DFT primary FPGA / ASIC Engineer pending
ATPG primary FPGA / ASIC Engineer pending
High-speed communication protocols FPGA / ASIC Engineer pending
Silicon bring-up FPGA / ASIC Engineer pending
R&R fragment (sim 0.00) FPGA / ASIC Engineer pending

• Generate test benches and test cases. • Perform RTL and gate-level SDF-annotated simulations and debug. • May perform mixed-signal (digital + analog) simulations and debug. • Interact with our appli…

Status: completed Created: 2026-05-27T15:59:00.573311Z Updated: 2026-06-12T15:40:47.698203Z API 3 duration: 20906 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

FPGA / ASIC Engineer

domain · Hardware Engineering CASE DOMAIN

slug: fpga-asic-engineer · id: 216 · source: db

Domain=Hardware Engineering; The JD centers on RTL, simulation/debug, physical verification, synthesis/timing tools, and chip design/verification for sensor IP, which best fits an FPGA/ASIC Engineer.

Matched skills

RTLgate-level SDF-annotated simulationsmixed-signal (digital + analog) simulationsCadence VirtuosoSynopsys Custom CompilerCalibreAssuraSynopsys Tool setFC/ICC2PrimetimeFormalityICVVerilogPERLPythonTCL

Matched dimensions

RTL and gate-level verificationMixed-signal simulation and debugPhysical verification and design rule checkingChip design and verificationCustomer support and application engineeringDocumentation and technical trainingQuality assurance improvementStatic timing analysis and synthesis

Matched KRAs

Generate test benches and test casesPerform RTL and gate-level SDF-annotated simulations and debugInteract with our application engineers and provide guidance to customersParticipate in the generation of data books, application notes, and white papersContribute to enhance quality assurance methodologyPerform physical verification and design rule checksStrengthen customer relationships through effective guidance and supportDrive continuous improvement in design methodologies and tools

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

We Are:

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation. PVT Sensor IP development is a critical offering for process, voltage, temperature and other monitoring IPs within SOC subsystem. Synopsys is the market leader for these IP developments which are integral parts of Silicon lifecycle monitoring.

You Are:

As a new, exciting and challenging position, we are looking for a talented person that can show a great level of initiative and ability to work in a busy and fast-changing environment. This rewarding role is fundamental to the successful and smooth operation of the engineering teams. You will play a vital role in helping to strengthen and develop forecasting capabilities, based on improved monitoring capacity and forward-looking project schedules.

What You’ll Be Doing:

• Generate test benches and test cases.
• Perform RTL and gate-level SDF-annotated simulations and debug.
• May perform mixed-signal (digital + analog) simulations and debug.
• Interact with our application engineers and provide guidance to customers.
• Participate in the generation of data books, application notes, and white papers.
• Contribute to enhance quality assurance methodology by adding more quality checks/gatings.
• Perform physical verification and design rule checks to ensure design integrity and manufacturability.


The Impact You Will Have:

• Enhance the quality and reliability of our PVT Sensor IPs.
• Improve project forecasting and monitoring capabilities.
• Support the development of innovative solutions for chip design and verification.
• Strengthen customer relationships through effective guidance and support.
• Contribute to knowledge sharing through documentation and training materials.
• Drive continuous improvement in design methodologies and tools.


What You’ll Need:

• Bachelor’s or master’s degree in electrical engineering or a related field.
• 3 to 7+ years of experience in A&MS frontend and backend views & collaterals development flows.
• Proficiency in industry-standard EDA tools, such as Cadence Virtuoso or Synopsys Custom Compiler.
• Exceptional knowledge of layout design methods, techniques, and methodologies.
• Experience with physical verification tools, such as Calibre or Assura.
• Understanding of semiconductor process technologies and their impact on layout design.


Who You Are:

We are seeking someone with excellent problem-solving and systematic skills, who can work effectively in a team-oriented environment. Familiarity with the Synopsys Tool set (such as FC/ICC2, Primetime, Formality, ICV) is essential. Good communication and interpersonal skills are a must. Experience in writing RTL Code, with solid Verilog, PERL, and Python skills, and TCL as an addition, will be highly valuable. Understanding of static timing analysis and synthesis, DFT/ATPG skills, and high-speed communication protocols are added advantages. Previous experience in customer support and/or silicon bring-up will be a plus.

The Team You’ll Be A Part Of:

You will be part of a dynamic and innovative team focused on developing and verifying high-performance silicon chips. Our team collaborates closely with design engineers and application engineers to ensure the successful integration and functionality of our IPs. We are committed to continuous improvement and knowledge sharing, contributing to the overall success of Synopsys and our customers.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

Skills from this JD

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

Verilog 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Perl Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Perl id=1001 · perl

Aliases — catalog

  • Perl (CANONICAL)

Context tags (catalog)

BioPerl CPAN Catalyst DBI Dancer Mojolicious Moose Object-Oriented Perl6 Perlbrew Plack Regex Template Toolkit Test::More Tidy

Stored enrichment (catalog DB)

Category
Language
Sub-category
Scripting Language
Vendor
Perl Foundation
License
unknown
Year introduced
1987
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Perl still appears in some legacy-maintenance JDs, but far fewer than Python/JavaScript; GitHub activity and new-project adoption are much lower, with many orgs having migrated to Python or Ruby.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
38
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)
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)
Tcl 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RTL 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
SDF-annotated simulation 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Mixed-signal simulation 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cadence Virtuoso 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Synopsys Custom Compiler 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Calibre 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Assura 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Physical verification 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Design rule checks 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
EDA tools 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
EDA Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Synopsys FC 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Synopsys ICC2 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
PrimeTime 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Formality 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ICV 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
EDA Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Static timing analysis 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Synthesis 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
DFT 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ATPG 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
EDA Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
High-speed communication protocols 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
Silicon bring-up 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
Practice
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
Perl in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Verilog | type=Programming Languages subtype=general nature=LANGUAGE lifespan=EVERGREEN
canonical_skill_proposed Tcl | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed RTL | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed SDF-annotated simulation | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Mixed-signal simulation | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Cadence Virtuoso | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Synopsys Custom Compiler | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Calibre | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Assura | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Physical verification | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Design rule checks | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed EDA tools | type=EDA Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Synopsys FC | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Synopsys ICC2 | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed PrimeTime | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Formality | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ICV | type=EDA Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Static timing analysis | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Synthesis | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed DFT | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed ATPG | type=EDA Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed High-speed communication protocols | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Silicon bring-up | type=Practice subtype=general nature=PRACTICE lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RolePVT Sensor IP Developer
CompanySynopsys
Experience3 to 7+ years of experience in A&MS frontend and backend views & collaterals development flows
DomainSoftware & SaaS Products
JD type pass
Show raw JSON
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API 1 — extract-from-jd click to toggle
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      },
      {
        "is_primary": true,
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        "is_primary": true,
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      {
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}
API 2 — extract-details
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        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Silicon bring-up",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practice",
          "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": "silicon-bring-up",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Verilog",
    "Tcl",
    "RTL",
    "SDF-annotated simulation",
    "Mixed-signal simulation",
    "Cadence Virtuoso",
    "Synopsys Custom Compiler",
    "Calibre",
    "Assura",
    "Physical verification",
    "Design rule checks",
    "EDA tools",
    "Synopsys FC",
    "Synopsys ICC2",
    "PrimeTime",
    "Formality",
    "ICV",
    "Static timing analysis",
    "Synthesis",
    "DFT",
    "ATPG",
    "High-speed communication protocols",
    "Silicon bring-up"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "FPGA / ASIC Engineer",
    "id": 216,
    "rationale": "Domain=Hardware Engineering; The JD centers on RTL, simulation/debug, physical verification, synthesis/timing tools, and chip design/verification for sensor IP, which best fits an FPGA/ASIC Engineer.",
    "role_archetype": null,
    "slug": "fpga-asic-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Verilog",
      "tag": "new"
    },
    {
      "skill": "Perl",
      "tag": "in_db"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Tcl",
      "tag": "new"
    },
    {
      "skill": "RTL",
      "tag": "new"
    },
    {
      "skill": "SDF-annotated simulation",
      "tag": "new"
    },
    {
      "skill": "Mixed-signal simulation",
      "tag": "new"
    },
    {
      "skill": "Cadence Virtuoso",
      "tag": "new"
    },
    {
      "skill": "Synopsys Custom Compiler",
      "tag": "new"
    },
    {
      "skill": "Calibre",
      "tag": "new"
    },
    {
      "skill": "Assura",
      "tag": "new"
    },
    {
      "skill": "Physical verification",
      "tag": "new"
    },
    {
      "skill": "Design rule checks",
      "tag": "new"
    },
    {
      "skill": "EDA tools",
      "tag": "new"
    },
    {
      "skill": "Synopsys FC",
      "tag": "new"
    },
    {
      "skill": "Synopsys ICC2",
      "tag": "new"
    },
    {
      "skill": "PrimeTime",
      "tag": "new"
    },
    {
      "skill": "Formality",
      "tag": "new"
    },
    {
      "skill": "ICV",
      "tag": "new"
    },
    {
      "skill": "Static timing analysis",
      "tag": "new"
    },
    {
      "skill": "Synthesis",
      "tag": "new"
    },
    {
      "skill": "DFT",
      "tag": "new"
    },
    {
      "skill": "ATPG",
      "tag": "new"
    },
    {
      "skill": "High-speed communication protocols",
      "tag": "new"
    },
    {
      "skill": "Silicon bring-up",
      "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": 216,
        "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"
        },
        "dimension_id": 96,
        "input_skill": "Perl",
        "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": [],
        "skill_dimension_saved": true,
        "skill_id": 1001,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 216,
        "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": 216,
        "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": 216,
        "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": 216,
        "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": 216,
        "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": 216,
        "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": 216,
        "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": 216,
        "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
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "7252e427-a97a-432b-967e-3f3f869cd9a0"
}

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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