Applied AI Engineer

- Design, build, and productionize resilient multi-agent execution graphs and advanced retrieval pipelines (hybrid search, semantic chunking, re-ranking, and graph-augmented RAG) built for deep reasoning over complex, large-scale codebases.

- Engineer low-latency, high-concurrency asynchronous backend services and microservices to integrate LLM reasoning into developer workflows, maintaining fault tolerance and rate-limiting.

- Implement continuous evaluation harnesses (hallucination detection, regression testing, task completion scoring) and optimize latency/cost trade-offs across proprietary APIs and fine-tuned open-source models using caching and speculative routing.

- Implement end-to-end tracing and observability pipelines for non-deterministic agent behavior (OpenTelemetry, Langfuse/Arize), driving high reliability and automated integration testing.

- Partner with frontend engineers, product architects, and security teams to translate raw model capabilities into deterministic, intuitive developer workflows.