via Ladders
$85K - 150K a year
Build and improve data pipelines, agentic coding retrieval agents, LLM prompt optimization, and backend services for PR/commit metadata and quality metrics.
Experience with agentic coding, data pipeline orchestration (Dagster or equivalent), LLM/prompt optimization, data modeling, backend integration, and eval/feedback loop design.
Senior Engineer (Agentic + Data/ML)_Remote Canada • 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. • Mandatory Skills Description: - 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.
This job posting was last updated on 4/21/2026