AI Engineering Consultant · [Add your company/client name]
Designing and deploying agentic AI systems for clients — multi-agent orchestration, tool-use architectures, retrieval-augmented generation, and the evaluation/observability layers that make them production-ready.
- Architected multi-agent systems (planner / executor / critic patterns) for complex task decomposition, tool calling, and reliable long-horizon execution.
- Built retrieval-augmented generation pipelines — hybrid search, reranking, and citation-grounded generation — to ground LLM output in client-specific data.
- Designed evaluation and observability tooling (offline eval sets, LLM-as-judge, tracing) to catch agent regressions before they reach production.
- Advised clients on generative AI strategy spanning data science, analytics, and applied ML adoption.