6+ years hands-on experience in ML/Applied AI (or equivalent), with strong Python fundamentals.
Proven experience building RAG applications in production (embedding models, vector search, reranking, prompt routing).
GCP proficiency: Vertex AI, BigQuery, Cloud Run or GKE, Cloud Build, Pub/Sub, GCS, IAM.
Frameworks: LangChain or similar (e.g., LlamaIndex, DSPy, Semantic Kernel).
Prompt engineering skills: few-shot design, tool calling, evaluation/guardrails.
Strong software practices: Git, CI/CD, typing, testing, code reviews, performance profiling.
Experience with vector DBs and retrieval services: Vertex AI Matching Engine, FAISS, Pinecone, Weaviate, Milvus, Chroma.
LLM providers & serving: Vertex AI, OpenAI, Anthropic, local (vLLMs), model gateways.
Evaluation & observability: RAGAS, TruLens, Promptfoo, LangSmith, Weights & Biases, Arize.
Agents/agentic frameworks; ADK (Agent Developer Kit) & Agentspace exposure is a plus.