Senior Engineer (Agentic + DataML)

Toronto - Canada

Monthly Salary: Not Disclosed

Posted on: 12 hours ago

Vacancies: 1 Vacancy

Job Summary

Responsibilities

CES improvements: PR-level scoring historical context context-retrieval agent automated score correction training data prep from feedback.
Data/PR tracking: ingest PRs link to commits/branches track merges to main backfills.
Orchestration & reliability: Dagster migration retries scheduling monitoring data quality alerts.
LLM/prompt optimization: DSPy-based prompt tuning eval set creation feedback-driven corrections prompt cost/quality tradeoffs.
Metadata & classification: role/work-type classification epic linking improvements filters/explorer features.

Skills Must have

Agentic coding: build retrieval agents that pull code context/diffs/history to improve scoring (aligns with CES Phase 3 and quality metric work).
Data pipelines: Dagster (preferred) or equivalent orchestrator; AWS-native pipelines (ECS/EventBridge/Lambda/S3/Glue experience a plus); robust backfills and retries.
LLM/Prompting: DSPy or similar prompt/policy optimization; prompt chaining; context packing; eval design and execution.
Data modeling & analytics: PR/commit linking branch/main tracking epic linking; quality/effort scoring signals; anomaly detection for data quality.
Backend integration: building services that ingest PR/commit metadata compute CES/quality metrics and expose them to UI/API.
Eval/feedback loops: design and run eval sets; collect user feedback; close the loop with automated/manual score correction

Responsibilities CES improvements: PR-level scoring historical context context-retrieval agent automated score correction training data prep from feedback. Data/PR tracking: ingest PRs link to commits/branches track merges to main backfills. Orchestration & reliability: Dagster migration retries sc...