Experience working with Bedrock Agent/Core services is a significant plus.
Candidates will be expected to demonstrate deep technical proficiency in the following areas:
Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators.
Expertise in latency optimization and relevance tuning to ensure production-grade performance.
Strategic approach to document chunking and embedding, balancing granularity with semantic coherence.
Practical experience developing autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel.
Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs.
Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing.
Familiarity with evaluation frameworks (e.g., RAGAS, TruLens) to assess performance, grounding accuracy, and hallucination detection.
Ability to iterate systems based on performance metrics and continuous improvement practices.

Gen AI Engineer

Summary