Pipeline run
e97fb735-0c34-4236-993f-8c665dddb330
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
Define Performance Testing processes Define & implement Performance test strategy for adopting microservices architecture & Cloud native applications Define holistic Application Performance strategy t…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Performance Test Engineer
domain · Testing & Quality CASE DOMAINslug: performance-test-engineer · id: 67 · source: db
Domain=Testing & Quality; The JD is centered on performance testing strategy, frameworks, resiliency, and performance engineering for cloud-native and microservices applications.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
About Wells Fargo Wells Fargo & Company (NYSE: WFC) is a leading global financial services company headquartered in San Francisco (United States). Wells Fargo has offices in over 20 countries and territories. Our business outside of the U.S. mostly focuses on providing banking services for large corporate, government and financial institution clients. We have worldwide expertise and services to help our customers improve earnings, manage risk, and develop opportunities in the global marketplace. Our global reach offers many opportunities for you to develop a career with Wells Fargo. Join our diverse and inclusive team where you will feel valued and inspired to contribute your unique skills and experience. We are looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you. About The Role Market Job Description Performance tester/engineer with proven experience in performance testing of web-based/client-server applications and backend testing Job Responsibilities Define Performance Testing processes Define & implement Performance test strategy for adopting microservices architecture & Cloud native applications Define holistic Application Performance strategy to identify design pattern & architecture flaws Design & Implement Enterprise Performance testing frameworks to support CI/CD pipeline Implement light weight, open source and cloud supported Performance testing frameworks Supporting Resiliency & Chaos Engineering strategies Implement & support Network & Service Virtualization Collaboratively work with application teams to implement Enterprise Monitoring & Logging standards w.r.to AppDynamics & Splunk Creates, prepares, and conducts SPLI quality assurance reviews and develops standard Test Methodology test plans Perform SPLI tests to ensure all deliverables are production ready and as per SLAs Provide technical guidance of performance testing to application developers, architects, business partners and management Troubleshoot and resolve Performance Engineering issues concurrently on multiple projects Have deep knowledge on Heap Memory and Garbage collection concepts and practical experience of configuring them Experience and Exposure to DevOps tools like Maven, GitHub, Udeploy, Artifactory, Sonar and Jenkins Be abreast of the Technological developments happening in the market and enlighten/educate the PT team Train new team members on Performance testing & Engineering and methodology Participate in driving initiatives within the Platform group Exposure and experience in Agile development life cycle May have to work in off hour shift starting from 1:30 PM to 10:30 PM Essential Qualifications Bachelors in Engineering or equivalent with minimum 8-12 years of experience with Performance testing /engineering using LoadRunner Very strong in scripting using VuGen is desired Knowledge on DevOps, Continuous Integration and Continuous Development activities Good to have Cloud based performance Testing experience Good to have certification on Load Runner or other performance Testing/Engineering tools and Application performance Monitoring tools Market Skills and Certifications We Value Diversity At Wells Fargo, we believe in diversity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We comply with all applicable laws in every jurisdiction in which we operate. Reference Number 62134BR
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- microservices (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Architecture
- Sub-category
- Distributed System Architecture
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.
Skill profile (library / DB)
- Skill nature
- PATTERN
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 1
- Sub-category id
- 1
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Microservices and Distributed Systems Catalog dimension db id 9
Library dimension (catalog)
Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Architectural Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- CI/CD (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Ci Cd Process
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 900
- 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 skipped (dimension not under chosen role) |
|
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Architectural Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Monitoring Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Splunk (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Observability Platform
- Vendor
- Splunk Inc.
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Splunk appears in many enterprise security/observability job descriptions and remains a common SIEM/log analytics platform; no vendor sunset or clear replacement has displaced it.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 176
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Observability and Incident Triage Catalog dimension db id 155
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
SIEM Products and Detection Engineering Languages Catalog dimension db id 62
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
SIEM Products and Detection Engineering Languages
siem-products-and-detection-engineering-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- Maven (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Build Tool
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2004
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Maven remains a standard Java build tool, appearing in many Java/JVM job descriptions and widely used in enterprise CI/CD pipelines alongside Gradle.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 358
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Build and Dependency Management Catalog dimension db id 286
Library dimension (catalog)
Roles linked in library: Java Backend Developer
-
Build and Packaging Tooling Catalog dimension db id 149
Library dimension (catalog)
Roles linked in library: DevOps Engineer, Ionic Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Build and Dependency Management
build-and-dependency-management
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Build and Packaging Tooling
build-and-packaging-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- GitHub (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Devops Platform
- Vendor
- GitHub, Inc.
- License
- other_open
- Year introduced
- 2008
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: GitHub appears in a very high volume of engineering JDs for source control, code review, and CI/CD; it’s a standard hiring-pipeline skill across teams.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 170
- 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 skipped (dimension not under chosen role) |
|
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Deployment Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- DevOps Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Testing Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Jenkins (CANONICAL) primary
Context tags (catalog)
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 skipped (dimension not under chosen role) |
|
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Agile (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Agile
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 3594
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
-
Software Concepts, Patterns & Practices Catalog dimension db id 478
Library dimension (catalog)
Roles linked in library: Engineering Manager
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
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 |
|---|---|---|---|---|---|---|
| Microservices | in_db |
Microservices and Distributed Systems
microservices-and-distributed-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Splunk | in_db |
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Splunk | in_db |
SIEM Products and Detection Engineering Languages
siem-products-and-detection-engineering-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Maven | in_db |
Build and Dependency Management
build-and-dependency-management
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Maven | in_db |
Build and Packaging Tooling
build-and-packaging-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GitHub | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GitHub | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Jenkins | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Jenkins | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Cloud Native | type=Architectural Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Resiliency | type=Architectural Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Chaos Engineering | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Service Virtualization | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | AppDynamics | type=Monitoring Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Test Methodology | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SLA | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Heap Memory | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Garbage Collection | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Udeploy | type=Deployment Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Artifactory | type=DevOps Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Sonar | type=Testing Tools subtype=general nature=TOOL lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Certifications
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Wells Fargo \u0026 Company (NYSE:",
"last_5_words": "with outstanding talent. It all"
},
"text": "Wells Fargo \u0026 Company (NYSE: WFC) is a leading global financial services company headquartered in San Francisco (United States). Wells Fargo has offices in over 20 countries and territories. Our business outside of the U.S. mostly focuses on providing banking services for large corporate, government and financial institution clients. We have worldwide expertise and services to help our customers improve earnings, manage risk, and develop opportunities in the global marketplace. Our global reach offers many opportunities for you to develop a career with Wells Fargo. Join our diverse and inclusive team where you will feel valued and inspired to contribute your unique skills and experience. We are looking for talented people who will put our customers at the center of everything we do. Help us build a better Wells Fargo. It all begins with outstanding talent. It all begins with you.",
"word_count": 108
},
"certifications": [
"Load Runner certification",
"performance Testing/Engineering tools certification",
"Application performance Monitoring tools certification"
],
"company_name": "Wells Fargo \u0026 Company",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"FinTech",
"Banking"
],
"domain": "Financial Services"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Engineering or equivalent",
"raw": "Bachelors in Engineering or equivalent",
"requirement": "required"
}
],
"experience": {
"max": 12,
"min": 8,
"raw": "minimum 8-12 years of experience with Performance testing /engineering"
},
"job_locations": [
{
"aliases": [
"SF"
],
"city": "San Francisco",
"country": "United States",
"state": "California",
"work_mode": "null"
}
],
"role": "Performance Tester/Engineer",
"role_aliases": [
"Performance Engineer",
"Performance Testing Engineer",
"Load Testing Engineer"
],
"role_archetype": "QA",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Job Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Define Performance Testing processes Define",
"last_5_words": "from 1:30 PM to 10:30 PM"
},
"text": "Define Performance Testing processes\nDefine \u0026 implement Performance test strategy for adopting microservices architecture \u0026 Cloud native applications\nDefine holistic Application Performance strategy to identify design pattern \u0026 architecture flaws\nDesign \u0026 Implement Enterprise Performance testing frameworks to support CI/CD pipeline\nImplement light weight, open source and cloud supported Performance testing frameworks\nSupporting Resiliency \u0026 Chaos Engineering strategies\nImplement \u0026 support Network \u0026 Service Virtualization\nCollaboratively work with application teams to implement Enterprise Monitoring \u0026 Logging standards w.r.to AppDynamics \u0026 Splunk\nCreates, prepares, and conducts SPLI quality assurance reviews and develops standard Test Methodology test plans\nPerform SPLI tests to ensure all deliverables are production ready and as per SLAs\nProvide technical guidance of performance testing to application developers, architects, business partners and management\nTroubleshoot and resolve Performance Engineering issues concurrently on multiple projects\nHave deep knowledge on Heap Memory and Garbage collection concepts and practical experience of configuring them\nExperience and Exposure to DevOps tools like Maven, GitHub, Udeploy, Artifactory, Sonar and Jenkins\nBe abreast of the Technological developments happening in the market and enlighten/educate the PT team\nTrain new team members on Performance testing \u0026 Engineering and methodology\nParticipate in driving initiatives within the Platform group\nExposure and experience in Agile development life cycle\nMay have to work in off hour shift starting from 1:30 PM to 10:30 PM",
"word_count": 290
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Microservices"
},
{
"is_primary": true,
"skill_name": "Cloud Native"
},
{
"is_primary": true,
"skill_name": "CI/CD"
},
{
"is_primary": true,
"skill_name": "Resiliency"
},
{
"is_primary": true,
"skill_name": "Chaos Engineering"
},
{
"is_primary": true,
"skill_name": "Service Virtualization"
},
{
"is_primary": true,
"skill_name": "AppDynamics"
},
{
"is_primary": true,
"skill_name": "Splunk"
},
{
"is_primary": true,
"skill_name": "Test Methodology"
},
{
"is_primary": true,
"skill_name": "SLA"
},
{
"is_primary": true,
"skill_name": "Heap Memory"
},
{
"is_primary": true,
"skill_name": "Garbage Collection"
},
{
"is_primary": true,
"skill_name": "Maven"
},
{
"is_primary": true,
"skill_name": "GitHub"
},
{
"is_primary": true,
"skill_name": "Udeploy"
},
{
"is_primary": true,
"skill_name": "Artifactory"
},
{
"is_primary": true,
"skill_name": "Sonar"
},
{
"is_primary": true,
"skill_name": "Jenkins"
},
{
"is_primary": true,
"skill_name": "Agile"
}
],
"jd_role": {
"display_name": "Performance Tester/Engineer",
"rationale": null,
"role_aliases": [
"Performance Engineer",
"Performance Testing Engineer",
"Load Testing Engineer"
],
"role_archetype": "QA",
"slug": ""
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API 2 — extract-details
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"slug": "devops-engineer",
"source": "db"
}
]
},
{
"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"
},
"input_skill": "GitHub",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
]
}
],
"input_skill": "GitHub",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Udeploy",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Deployment Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "udeploy",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Artifactory",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "DevOps Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "artifactory",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Sonar",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Testing Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "sonar",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Jenkins",
"alias_type": "CANONICAL",
"id": 544,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 13,
"display_name": "Jenkins",
"id": 283,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "jenkins",
"sub_category_id": 184,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"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"
},
"input_skill": "Jenkins",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
]
},
{
"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"
},
"input_skill": "Jenkins",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
]
}
],
"input_skill": "Jenkins",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Agile",
"alias_type": "CANONICAL",
"id": 868,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "Agile",
"id": 520,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "agile",
"sub_category_id": 3594,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Agile",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Software Concepts, Patterns \u0026 Practices",
"id": 478,
"rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
"slug": "software-concepts-patterns-practices",
"source": "db"
},
"input_skill": "Agile",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
}
],
"input_skill": "Agile",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Cloud Native",
"Resiliency",
"Chaos Engineering",
"Service Virtualization",
"AppDynamics",
"Test Methodology",
"SLA",
"Heap Memory",
"Garbage Collection",
"Udeploy",
"Artifactory",
"Sonar"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Performance Test Engineer",
"id": 67,
"rationale": "Domain=Testing \u0026 Quality; The JD is centered on performance testing strategy, frameworks, resiliency, and performance engineering for cloud-native and microservices applications.",
"role_archetype": null,
"slug": "performance-test-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Microservices",
"tag": "in_db"
},
{
"skill": "Cloud Native",
"tag": "new"
},
{
"skill": "CI/CD",
"tag": "in_db"
},
{
"skill": "Resiliency",
"tag": "new"
},
{
"skill": "Chaos Engineering",
"tag": "new"
},
{
"skill": "Service Virtualization",
"tag": "new"
},
{
"skill": "AppDynamics",
"tag": "new"
},
{
"skill": "Splunk",
"tag": "in_db"
},
{
"skill": "Test Methodology",
"tag": "new"
},
{
"skill": "SLA",
"tag": "new"
},
{
"skill": "Heap Memory",
"tag": "new"
},
{
"skill": "Garbage Collection",
"tag": "new"
},
{
"skill": "Maven",
"tag": "in_db"
},
{
"skill": "GitHub",
"tag": "in_db"
},
{
"skill": "Udeploy",
"tag": "new"
},
{
"skill": "Artifactory",
"tag": "new"
},
{
"skill": "Sonar",
"tag": "new"
},
{
"skill": "Jenkins",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
}
],
"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": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Microservices and Distributed Systems",
"id": 9,
"rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
"slug": "microservices-and-distributed-systems",
"source": "db"
},
"dimension_id": 9,
"input_skill": "Microservices",
"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": "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": 41,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"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": "CI/CD",
"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": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 1190,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
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"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
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},
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"input_skill": "CI/CD",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1190,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Triage",
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"rationale": "Telemetry, alerting, and troubleshooting practices used to diagnose failed builds, broken deployments, and unhealthy release environments. This is a coherent cluster because delivery reliability depends on quickly identifying where the workflow failed.",
"slug": "observability-and-incident-triage",
"source": "db"
},
"dimension_id": 155,
"input_skill": "Splunk",
"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": "DevOps Engineer",
"id": 10,
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"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 315,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "SIEM Products and Detection Engineering Languages",
"id": 62,
"rationale": "Security monitoring platforms and the query/rule languages used to build detections, hunts, and alert triage workflows. This dimension stays separate because the role often works across multiple SIEM products and their native query syntaxes.",
"slug": "siem-products-and-detection-engineering-languages",
"source": "db"
},
"dimension_id": 62,
"input_skill": "Splunk",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 315,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Build and Dependency Management",
"id": 286,
"rationale": "Project build, packaging, and dependency resolution skills used to compile and assemble Java services. This cluster matters because backend delivery depends on reproducible builds and controlled library versions.",
"slug": "build-and-dependency-management",
"source": "db"
},
"dimension_id": 286,
"input_skill": "Maven",
"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": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 815,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Build and Packaging Tooling",
"id": 149,
"rationale": "Tooling used to compile, package, and prepare Ionic apps for development and release. This cluster is coherent because Ionic developers often manage web assets, native wrappers, and environment-specific build outputs.",
"slug": "build-and-packaging-tooling",
"source": "db"
},
"dimension_id": 149,
"input_skill": "Maven",
"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": "DevOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Ionic Developer",
"id": 434,
"rationale": null,
"role_archetype": null,
"slug": "ionic-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 815,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD Pipeline Platforms",
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"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": "GitHub",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
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"role_archetype": null,
"slug": "devops-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 280,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
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"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
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},
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"input_skill": "GitHub",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 280,
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},
{
"chosen_role_id": 67,
"dimension": {
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"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.",
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"source": "db"
},
"dimension_id": 150,
"input_skill": "Jenkins",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
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"role_archetype": null,
"slug": "devops-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 283,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
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"difficulty_hint": "well_known",
"display_name": "CI/CD for Machine Learning",
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"rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
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},
"dimension_id": 56,
"input_skill": "Jenkins",
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"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
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}
],
"skill_dimension_saved": true,
"skill_id": 283,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"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": "Agile",
"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": 520,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 67,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Software Concepts, Patterns \u0026 Practices",
"id": 478,
"rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
"slug": "software-concepts-patterns-practices",
"source": "db"
},
"dimension_id": 478,
"input_skill": "Agile",
"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",
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"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 520,
"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": "e97fb735-0c34-4236-993f-8c665dddb330"
}