Found Description
- Strong Python, plus solid API/backend skills (FastAPI, async, request handling)
- LLM application patterns: prompting, RAG (retrieval-augmented generation), function/tool calling, structured outputs, evaluation harnesses
- Working with model APIs (Anthropic, OpenAI, etc.) and frameworks like LangChain, LlamaIndex, or DSPy
- Vector databases and embeddings (Pinecone, Weaviate, pgvector, FAISS)
- Orchestration of multi-step / agentic workflows
- Evaluation and observability (tracing, prompt/version management, offline + online eval)
- Cost/latency optimization, caching, streaming
- Basic ML literacy (you don't train models, but you need to understand them)
- Guardrails, safety, and handling hallucination/failure modes
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