Pipeline run
c467cd6f-07de-4eb6-9810-5c5c2117b4ae
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
We're a small but ambitious team. Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms o…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Quantum Computing Engineer
CASE Aslug: quantum-computing-engineer · id: 213 · source: db
Exact alias hit on quantum-computing-engineer (1.0) — no other alias at this confidence; skill_top absent does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Senior Quantum Algorithms Engineer — full-time role, hybrid (Bengaluru). We're a small but ambitious team. Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum). Strong linear algebra + numerical methods background required. Experience with QASM, Pulse-level control, or hybrid quantum-classical hyperparameter tuning is a plus.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
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
- 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
- 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
- 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
- Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- 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
- Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- 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
- Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- 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
- 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
- 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
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Quantum Algorithms | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | VQE | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | QAOA | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Qiskit | type=Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Cirq | type=Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | IBM Quantum | type=Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | IonQ | type=Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Quantinuum | type=Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Linear Algebra | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Numerical Methods | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | QASM | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Pulse | type=Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Hybrid Quantum-Classical Hyperparameter Tuning | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": null,
"raw": null
},
"job_locations": [
{
"aliases": [
"Bangalore"
],
"city": "Bengaluru",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Senior Quantum Algorithms Engineer",
"role_aliases": [
"Quantum Algorithms Engineer",
"Quantum Engineer",
"Quantum Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Role Overview",
"heading_was_present": false,
"source_marker": {
"first_5_words": "We\u0027re a small but ambitious",
"last_5_words": "or hybrid quantum-classical hyperparameter tuning is a plus."
},
"text": "We\u0027re a small but ambitious team. Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum). Strong linear algebra + numerical methods background required. Experience with QASM, Pulse-level control, or hybrid quantum-classical hyperparameter tuning is a plus.",
"word_count": 64
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Quantum Algorithms"
},
{
"is_primary": true,
"skill_name": "VQE"
},
{
"is_primary": true,
"skill_name": "QAOA"
},
{
"is_primary": true,
"skill_name": "Qiskit"
},
{
"is_primary": true,
"skill_name": "Cirq"
},
{
"is_primary": true,
"skill_name": "IBM Quantum"
},
{
"is_primary": true,
"skill_name": "IonQ"
},
{
"is_primary": true,
"skill_name": "Quantinuum"
},
{
"is_primary": true,
"skill_name": "Linear Algebra"
},
{
"is_primary": true,
"skill_name": "Numerical Methods"
},
{
"is_primary": false,
"skill_name": "QASM"
},
{
"is_primary": false,
"skill_name": "Pulse"
},
{
"is_primary": false,
"skill_name": "Hybrid Quantum-Classical Hyperparameter Tuning"
}
],
"jd_role": {
"display_name": "Senior Quantum Algorithms Engineer",
"rationale": null,
"role_aliases": [
"Quantum Algorithms Engineer",
"Quantum Engineer",
"Quantum Software Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": null,
"raw": null
},
"job_locations": [
{
"aliases": [
"Bangalore"
],
"city": "Bengaluru",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Senior Quantum Algorithms Engineer",
"role_aliases": [
"Quantum Algorithms Engineer",
"Quantum Engineer",
"Quantum Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Role Overview",
"heading_was_present": false,
"source_marker": {
"first_5_words": "We\u0027re a small but ambitious",
"last_5_words": "or hybrid quantum-classical hyperparameter tuning is a plus."
},
"text": "We\u0027re a small but ambitious team. Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum). Strong linear algebra + numerical methods background required. Experience with QASM, Pulse-level control, or hybrid quantum-classical hyperparameter tuning is a plus.",
"word_count": 64
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "c467cd6f-07de-4eb6-9810-5c5c2117b4ae",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Quantum Computing Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 213,
"score": 1.0,
"slug": "quantum-computing-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Cyber Security Engineer",
"kra_matches": [
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Strong linear algebra + numerical methods background required.",
"similarity": 0.2772
},
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum).",
"similarity": 0.2744
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 5,
"score": 0.2758,
"slug": "cybersecurity-engineer",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Strong linear algebra + numerical methods background required.",
"similarity": 0.2906
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum).",
"similarity": 0.2606
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.2756,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "ML Engineer",
"kra_matches": [
{
"kra_text": "Translates product requirements into machine learning system specifications including feature definitions, model architecture choices, and success metric definitions.",
"sentence": "Strong linear algebra + numerical methods background required.",
"similarity": 0.3098
},
{
"kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
"sentence": "Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum).",
"similarity": 0.2373
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 3,
"score": 0.2736,
"slug": "ml-engineer",
"total_count": null
},
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Optimizes pipeline throughput, partitioning strategies, and query performance across cloud data warehouses like Snowflake, BigQuery, or Redshift.",
"sentence": "Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum).",
"similarity": 0.2776
},
{
"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": "Strong linear algebra + numerical methods background required.",
"similarity": 0.2519
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.2648,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "AI Engineer",
"kra_matches": [
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms on real QPUs (IBM Quantum, IonQ, Quantinuum).",
"similarity": 0.2903
},
{
"kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
"sentence": "Strong linear algebra + numerical methods background required.",
"similarity": 0.2208
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 13,
"score": 0.2555,
"slug": "ai-engineer",
"total_count": null
}
],
"skill_match_roles": []
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Quantum Computing Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 213,
"score": 1.0,
"slug": "quantum-computing-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on quantum-computing-engineer (1.0) \u2014 no other alias at this confidence; skill_top absent does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 4,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 133,
"r_and_r_preview": "We\u0027re a small but ambitious team. Apply if you have published work on near-term quantum algorithms (VQE, QAOA, fault-tolerant variants), comfortable in Qiskit / Cirq, and have benchmarked algorithms o",
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 3530,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Quantum Algorithms",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3531,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "VQE",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3532,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "QAOA",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3533,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Qiskit",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3534,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Cirq",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3535,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "IBM Quantum",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3536,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "IonQ",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3537,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Quantinuum",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3538,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Linear Algebra",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 3539,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Numerical Methods",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3540,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "QASM",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3541,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Pulse",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 3542,
"role_display_name": "Quantum Computing Engineer",
"role_slug": "quantum-computing-engineer",
"skill_name": "Hybrid Quantum-Classical Hyperparameter Tuning",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [],
"candidate_roles": [],
"chosen_role": {
"display_name": "Quantum Computing Engineer",
"id": null,
"rationale": "Exact alias hit on quantum-computing-engineer (1.0) \u2014 no other alias at this confidence; skill_top absent does not contradict",
"role_archetype": "Engineering",
"slug": "quantum-computing-engineer",
"source": "llm"
},
"dimensions": [],
"input_final_skills": [
"Quantum Algorithms",
"VQE",
"QAOA",
"Qiskit",
"Cirq",
"IBM Quantum",
"IonQ",
"Quantinuum",
"Linear Algebra",
"Numerical Methods",
"QASM",
"Pulse",
"Hybrid Quantum-Classical Hyperparameter Tuning"
],
"input_llm_skills": [
"Quantum Algorithms",
"VQE",
"QAOA",
"Qiskit",
"Cirq",
"IBM Quantum",
"IonQ",
"Quantinuum",
"Linear Algebra",
"Numerical Methods",
"QASM",
"Pulse",
"Hybrid Quantum-Classical Hyperparameter Tuning"
],
"new_aliases_persisted": 0,
"run_id": "c467cd6f-07de-4eb6-9810-5c5c2117b4ae",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Quantum Algorithms",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "quantum-algorithms",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "VQE",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "vqe",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "QAOA",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "qaoa",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Qiskit",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "qiskit",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Cirq",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "cirq",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "IBM Quantum",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "ibm-quantum",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "IonQ",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "ionq",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Quantinuum",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "quantinuum",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Linear Algebra",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
"volatility": "STABLE"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "linear-algebra",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Numerical Methods",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "numerical-methods",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "QASM",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "qasm",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Pulse",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "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": "pulse",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Hybrid Quantum-Classical Hyperparameter Tuning",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "hybrid-quantum-classical-hyperparameter-tuning",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Quantum Algorithms",
"VQE",
"QAOA",
"Qiskit",
"Cirq",
"IBM Quantum",
"IonQ",
"Quantinuum",
"Linear Algebra",
"Numerical Methods",
"QASM",
"Pulse",
"Hybrid Quantum-Classical Hyperparameter Tuning"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Quantum Computing Engineer",
"id": 213,
"rationale": "Exact alias hit on quantum-computing-engineer (1.0) \u2014 no other alias at this confidence; skill_top absent does not contradict",
"role_archetype": "Engineering",
"slug": "quantum-computing-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Quantum Algorithms",
"tag": "new"
},
{
"skill": "VQE",
"tag": "new"
},
{
"skill": "QAOA",
"tag": "new"
},
{
"skill": "Qiskit",
"tag": "new"
},
{
"skill": "Cirq",
"tag": "new"
},
{
"skill": "IBM Quantum",
"tag": "new"
},
{
"skill": "IonQ",
"tag": "new"
},
{
"skill": "Quantinuum",
"tag": "new"
},
{
"skill": "Linear Algebra",
"tag": "new"
},
{
"skill": "Numerical Methods",
"tag": "new"
},
{
"skill": "QASM",
"tag": "new"
},
{
"skill": "Pulse",
"tag": "new"
},
{
"skill": "Hybrid Quantum-Classical Hyperparameter Tuning",
"tag": "new"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "c467cd6f-07de-4eb6-9810-5c5c2117b4ae"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.