Pipeline run
073e4db4-3521-41ed-87f9-2aba6d0fae20
Pipeline LLM cost (USD)
API 1: $0.0068
API 2: $0.0003
API 3: $0.0000
Total: $0.0071
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded
sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work
· Data platform optimization and governance
Build and evolve AWS-based data pipelines and models using tools like Redshift, Kinesis, EMR, Lambda, DataNet and QuickSight, while improving architecture for scale, quality, monitoring and security and defining data governance controls.
"Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security."
Tech stack maturity
Mainstream Modern
AWS and Redshift are widely adopted cloud data-platform technologies that indicate a modern, cloud-based stack without implying bleeding-edge specialization.
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 (8)
AWS
Redshift
Kinesis
EMR
Lambda
QuickSight
DataNet
Cradle
Skill cluster (2 dimension groups, role-scoped)
Cloud Platforms
AWS
Redshift
Cross-cutting / unaligned
Kinesis
EMR
Lambda
QuickSight
DataNet
Cradle
Show KRA description ↓
• Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (DataNet, Cradle, Quick Sight etc.
• Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.
• Develop new data models and end to data pipelines.
• Create and implement Data Governance strategy for mitigating privacy and security risks.
Signals
Skill
backend-engineer
0.25
Alias
data-engineer
1.00
KRA
data-engineer
0.57
Post-classification
Centroidupdated · n=161
Alias collision log—
New-role queue—
New skills captured6
New KRA captured—
Captured for admin review
Kinesis
primary
↔
Data Engineer
pending
EMR
primary
↔
Data Engineer
pending
Lambda
primary
↔
Data Engineer
pending
QuickSight
primary
↔
Data Engineer
pending
DataNet
primary
↔
Data Engineer
pending
Cradle
primary
↔
Data Engineer
pending
Status:
completed
Created: 2026-05-27T14:21:10.598059Z
Updated: 2026-05-27T14:22:18.549772Z
API 3 duration: 22686 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
Data Engineer
domain · Data Engineering & Analytics CASE DOMAINslug: data-engineer · id: 2 · source: db
Domain=Data Engineering & Analytics; The JD focuses on building data products, infrastructure, pipelines, and end-to-end data architecture on AWS, which best matches a Data Engineer role.
Matched skills
AWSRedshiftKinesisEMRLambdaDataNetCradleQuick SightData GovernanceData Architecture
Matched dimensions
Data Pipeline EngineeringData Infrastructure DevelopmentCloud Data EngineeringData ModelingData Governance and SecurityData Quality and Monitoring
Matched KRAs
Develop data products, infrastructure and data pipelinesImprove existing solutions and come up with next generation Data ArchitectureDevelop new data models and end to end data pipelinesCreate and implement Data Governance strategyMitigate privacy and security risks
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
This job is with Amazon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Description Are you passionate about data and code? Does the prospect of dealing with mission-critical data excite you? Do you want to build data engineering solutions that process a broad range of business and customer data? Do you want to continuously improve the systems that enable annual worldwide revenue of hundreds of billions of dollars? If so, then the eCommerce Services (eCS) team is for you! In eCommerce Services (eCS), we build systems that span the full range of eCommerce functionality, from Privacy, Identity, Purchase Experience and Ordering to Shipping, Tax and Financial integration. eCommerce Services manages several aspects of the customer life cycle, starting from account creation and sign in, to placing items in the shopping cart, proceeding through checkout, order processing, managing order history and post-fulfillment actions such as refunds and tax invoices. eCS services determine sales tax and shipping charges, and we ensure the privacy of our customers. Our mission is to provide a commerce foundation that accelerates business innovation and delivers a secure, available, performant, and reliable shopping experience to Amazon's customers. The goal of the eCS Data Engineering and Analytics team is to provide high quality, on-time reports to Amazon business teams, enabling them to expand globally at scale. Our team has a direct impact on retail CX, a key component that runs our Amazon fly wheel. As a Data Engineer, you will own the architecture of DW solutions for the Enterprise using multiple platforms. You would have the opportunity to lead the design, creation and management of extremely large datasets working backwards from business use cases. You will use your strong business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics. You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business demand for data and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. Key job responsibilities • Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (DataNet, Cradle, Quick Sight etc. • Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security. • Develop new data models and end to data pipelines. • Create and implement Data Governance strategy for mitigating privacy and security risks. Basic Qualifications • 3+ years of data engineering experience • Experience with data modeling, warehousing and building ETL pipelines • Experience with SQL Preferred Qualifications • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
AWS
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: AWS
id=187
· aws
Aliases — catalog
- AWS (CANONICAL) primary
Context tags (catalog)
API Gateway
AWS CLI
Auto Scaling
CloudFormation
CloudFront
CloudTrail
CloudWatch
Cognito
DynamoDB
EC2
ECS
EKS
Elastic Beanstalk
Elastic Load Balancing
IAM
KMS
Lambda
RDS
Route 53
S3
SNS
SQS
Serverless
VPC
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Platform
- Vendor
- Amazon
- License
- other_open
- Year introduced
- 2006
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 46
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms for AI Deployment Catalog dimension db id 211
Library dimension (catalog)
Roles linked in library: AI Engineer
-
Cloud Provider Platforms Catalog dimension db id 131
Library dimension (catalog)
Roles linked in library: Cloud Architect, Cloud Security Engineer
-
Cloud Security Posture Tools Catalog dimension db id 64
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Redshift
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: Redshift
id=1210
· redshift
Aliases — catalog
- Redshift (CANONICAL)
Context tags (catalog)
AWS
Amazon S3
ETL
Redshift Spectrum
SQL
analytics
business intelligence
cluster management
columnar storage
data lake
data migration
data modeling
data warehousing
performance tuning
query optimization
scalability
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Warehouse Platform
- Vendor
- Amazon
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Amazon Redshift is widely listed in data-warehouse/cloud analytics job descriptions and remains an AWS flagship service; no vendor sunset, and it’s commonly paired with Snowflake/BigQuery rather than replaced.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 917
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Kinesis
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
EMR
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Lambda
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
QuickSight
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
DataNet
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
Cradle
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
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
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 |
|---|---|---|---|---|---|---|
| AWS | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| AWS | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Redshift | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Kinesis | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | EMR | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Lambda | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | QuickSight | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | DataNet | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=SHORT_LIVED | |
| canonical_skill_proposed | Cradle | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=SHORT_LIVED |
nano JD Parser — gpt-4.1-nano click to toggle
RoleData Engineer
CompanyAmazon
Experience3+ years of data engineering experience
DomainE-commerce
JD type
pass
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "Amazon",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Online Retail",
"Marketplaces"
],
"domain": "E-commerce"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 3,
"raw": "3+ years of data engineering experience"
},
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Data Developer",
"ETL Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 4,
"heading": "Key job responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Develop data products, infrastructure",
"last_5_words": "privacy and security risks."
},
"text": "\u2022 Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (DataNet, Cradle, Quick Sight etc.\n\u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.\n\u2022 Develop new data models and end to data pipelines.\n\u2022 Create and implement Data Governance strategy for mitigating privacy and security risks.",
"word_count": 56
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "AWS"
},
{
"is_primary": true,
"skill_name": "Redshift"
},
{
"is_primary": true,
"skill_name": "Kinesis"
},
{
"is_primary": true,
"skill_name": "EMR"
},
{
"is_primary": true,
"skill_name": "Lambda"
},
{
"is_primary": true,
"skill_name": "QuickSight"
},
{
"is_primary": true,
"skill_name": "DataNet"
},
{
"is_primary": true,
"skill_name": "Cradle"
}
],
"jd_role": {
"display_name": "Data Engineer",
"rationale": null,
"role_aliases": [
"Data Engineer",
"Data Developer",
"ETL Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": "Amazon",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Online Retail",
"Marketplaces"
],
"domain": "E-commerce"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 3,
"raw": "3+ years of data engineering experience"
},
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Data Developer",
"ETL Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 4,
"heading": "Key job responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Develop data products, infrastructure",
"last_5_words": "privacy and security risks."
},
"text": "\u2022 Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc.) and internal BDT tools (DataNet, Cradle, Quick Sight etc.\n\u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.\n\u2022 Develop new data models and end to data pipelines.\n\u2022 Create and implement Data Governance strategy for mitigating privacy and security risks.",
"word_count": 56
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "073e4db4-3521-41ed-87f9-2aba6d0fae20",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Develop new data models and end to data pipelines.",
"similarity": 0.6157
},
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc. ) and internal BDT tools (DataNet, Cradle, Quick Sight etc. \u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.",
"similarity": 0.5807
},
{
"kra_text": "Maintains data catalog entries, column-level data lineage, and technical documentation to support data discoverability and governance across the organization.",
"sentence": "Create and implement Data Governance strategy for mitigating privacy and security risks.",
"similarity": 0.5097
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5687,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Cloud Security Engineer",
"kra_matches": [
{
"kra_text": "Designs and implements cloud security controls including KMS encryption, secrets management, and data-at-rest protection for AWS, Azure, or GCP workloads.",
"sentence": "Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc. ) and internal BDT tools (DataNet, Cradle, Quick Sight etc. \u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.",
"similarity": 0.5177
},
{
"kra_text": "Configures cloud data protection including column-level encryption, DLP scanning policies, and data classification labels for regulated data.",
"sentence": "Create and implement Data Governance strategy for mitigating privacy and security risks.",
"similarity": 0.5018
},
{
"kra_text": "Configures cloud data protection including column-level encryption, DLP scanning policies, and data classification labels for regulated data.",
"sentence": "Develop new data models and end to data pipelines.",
"similarity": 0.3502
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 23,
"score": 0.4566,
"slug": "cloud-security-engineer",
"total_count": null
},
{
"display_name": "Svelte Frontend Developer",
"kra_matches": [
{
"kra_text": "backend data integration",
"sentence": "Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc. ) and internal BDT tools (DataNet, Cradle, Quick Sight etc. \u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.",
"similarity": 0.5104
},
{
"kra_text": "backend data integration",
"sentence": "Develop new data models and end to data pipelines.",
"similarity": 0.468
},
{
"kra_text": "backend data integration",
"sentence": "Create and implement Data Governance strategy for mitigating privacy and security risks.",
"similarity": 0.363
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 92,
"score": 0.4471,
"slug": "svelte-frontend-developer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Establishes cloud governance guardrails including budget alerts, resource quotas, policy-as-code enforcement, and compliance posture management.",
"sentence": "Create and implement Data Governance strategy for mitigating privacy and security risks.",
"similarity": 0.4765
},
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc. ) and internal BDT tools (DataNet, Cradle, Quick Sight etc. \u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.",
"similarity": 0.4607
},
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "Develop new data models and end to data pipelines.",
"similarity": 0.3707
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.436,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "Develop new data models and end to data pipelines.",
"similarity": 0.5108
},
{
"kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
"sentence": "Develop data products, infrastructure and data pipelines leveraging AWS services (such as Redshift, Kinesis, EMR, Lambda etc. ) and internal BDT tools (DataNet, Cradle, Quick Sight etc. \u2022 Improve existing solutions and come up with next generation Data Architecture to improve scale, quality, timeliness, coverage, monitoring and security.",
"similarity": 0.4525
},
{
"kra_text": "Manages model versioning, shadow deployments, A/B test rollouts, and safe rollback procedures using MLflow or SageMaker model registry.",
"sentence": "Create and implement Data Governance strategy for mitigating privacy and security risks.",
"similarity": 0.3169
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.4267,
"slug": "ml-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Redshift"
],
"role_id": 1,
"score": 0.25,
"slug": "backend-engineer",
"total_count": 8
},
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Redshift"
],
"role_id": 3,
"score": 0.25,
"slug": "ml-engineer",
"total_count": 8
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Redshift"
],
"role_id": 5,
"score": 0.25,
"slug": "cybersecurity-engineer",
"total_count": 8
},
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Redshift"
],
"role_id": 2,
"score": 0.25,
"slug": "data-engineer",
"total_count": 8
},
{
"display_name": "DevOps Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Redshift"
],
"role_id": 10,
"score": 0.25,
"slug": "devops-engineer",
"total_count": 8
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.98,
"slug": "data-engineer",
"total_count": null
},
"confidence": 0.98,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Data Pipeline Engineering",
"Data Infrastructure Development",
"Cloud Data Engineering",
"Data Modeling",
"Data Governance and Security",
"Data Quality and Monitoring"
],
"matched_kras": [
"Develop data products, infrastructure and data pipelines",
"Improve existing solutions and come up with next generation Data Architecture",
"Develop new data models and end to end data pipelines",
"Create and implement Data Governance strategy",
"Mitigate privacy and security risks"
],
"matched_skills": [
"AWS",
"Redshift",
"Kinesis",
"EMR",
"Lambda",
"DataNet",
"Cradle",
"Quick Sight",
"Data Governance",
"Data Architecture"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Data Engineering \u0026 Analytics; The JD focuses on building data products, infrastructure, pipelines, and end-to-end data architecture on AWS, which best matches a Data Engineer role.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 161,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 8480,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Kinesis",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8481,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "EMR",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8482,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Lambda",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8483,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "QuickSight",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8484,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "DataNet",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 8485,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Cradle",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
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{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 406,
"existing_alias_text": "AWS",
"input_term": "AWS",
"matched_canonical": {
"category_id": 9,
"display_name": "AWS",
"id": 187,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "aws",
"sub_category_id": 46,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1846,
"existing_alias_text": "Redshift",
"input_term": "Redshift",
"matched_canonical": {
"category_id": 9,
"display_name": "Redshift",
"id": 1210,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "redshift",
"sub_category_id": 917,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
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},
{
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"slug": "backend-engineer",
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},
{
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"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
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"slug": "devops-engineer",
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},
{
"display_name": "Fullstack Developer",
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"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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},
{
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},
{
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"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
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},
{
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"slug": "ml-engineer",
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},
{
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"slug": "ml-ops-engineer",
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},
{
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"slug": "node-backend-developer",
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},
{
"display_name": "Python Backend Developer",
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"role_archetype": "Engineering",
"slug": "python-backend-developer",
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},
{
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"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
},
{
"display_name": "AI Engineer",
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"slug": "ai-engineer",
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},
{
"display_name": "Cloud Architect",
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"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
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}
],
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},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
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},
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"roles_from_db": [
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},
{
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{
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{
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{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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]
},
{
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},
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]
},
{
"dimension": {
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},
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{
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]
},
{
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]
},
{
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{
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{
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{
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]
}
],
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"input_llm_skills": [
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"run_id": "073e4db4-3521-41ed-87f9-2aba6d0fae20",
"skills_detail": [
{
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],
"canonical": {
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},
{
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{
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},
{
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"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
}
],
"input_skill": "AWS",
"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": "Redshift",
"alias_type": "CANONICAL",
"id": 1846,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Redshift",
"id": 1210,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "redshift",
"sub_category_id": 917,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"input_skill": "Redshift",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "Redshift",
"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": "Kinesis",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"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": "kinesis",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "EMR",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"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": "emr",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Lambda",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"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": "lambda",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "QuickSight",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"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": "quicksight",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "DataNet",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "datanet",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Cradle",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "cradle",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Kinesis",
"EMR",
"Lambda",
"QuickSight",
"DataNet",
"Cradle"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD focuses on building data products, infrastructure, pipelines, and end-to-end data architecture on AWS, which best matches a Data Engineer role.",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Redshift",
"tag": "in_db"
},
{
"skill": "Kinesis",
"tag": "new"
},
{
"skill": "EMR",
"tag": "new"
},
{
"skill": "Lambda",
"tag": "new"
},
{
"skill": "QuickSight",
"tag": "new"
},
{
"skill": "DataNet",
"tag": "new"
},
{
"skill": "Cradle",
"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": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 187,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms for AI Deployment",
"id": 211,
"rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
"slug": "cloud-platforms-for-ai-deployment",
"source": "db"
},
"dimension_id": 211,
"input_skill": "AWS",
"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": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 187,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"dimension_id": 131,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 187,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"dimension_id": 64,
"input_skill": "AWS",
"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"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 187,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "Redshift",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1210,
"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": "073e4db4-3521-41ed-87f9-2aba6d0fae20"
}
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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