AI Engineer

+ Build and deploy LLM-powered agents for enterprise data validation — reading specs, reasoning about business rules, identifying failure modes, and generating structured outputs

+ Design and own evaluation frameworks: automated test suites, LLM-as-judge pipelines, regression detection, and benchmarks that track whether our agents are improving

+ Build RAG pipelines that work reliably on real enterprise data — messy schemas, inconsistent formats, mixed structured and unstructured content

+ Integrate AI systems with enterprise infrastructure (SAP, Snowflake, Databricks, Postgres, REST APIs) with attention to latency, data residency, and compliance

+ Design agentic workflows with tool use, multi-step reasoning, and deterministic guardrails

+ Build observability tooling: trace agent reasoning, track output reliability, and detect hallucinations or drift in production

+ Work directly with FDSEs to understand real deployment failures and translate them into system improvements