Senior level (typically 8+ years in software or ML engineering) with a track record of multiple systems shipped to production and run in live use. Be ready to walk us through them: what you built, what failed, what you changed.
Production Python (3.12): typed, packaged, tested code (pytest, ruff, pre-commit), clean module structure, no notebook-only work.
Agents built on Claude (Claude Agent SDK or Claude Code, tool use, prompt design, structured outputs), with experience keeping long agent sessions reliable and detecting when an agent stops early or invents output.
Multi-agent systems in production: orchestration, parallelism, dependency ordering, independent verification, failure handling, cost control. Evidence from live systems, not only demos.
Testing and evaluating LLM systems: fake or recorded backends, deterministic tests for the surrounding code, separate evals for model output.
Git and CI/CD at team scale: pull-request workflow, GitHub Actions or Azure DevOps pipelines, Docker, versioned releases.
Cloud and data: PostgreSQL (schema design, migrations, audit tables), Azure Data Lake Storage / Blob, Parquet, pandas/pyarrow.
GxP delivery: you have built or supported software under validation: traceability from requirement to test, audit trails, change control, access control, documentation.
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