AI Developer
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Role details
Tech stack
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Requirements
7 10+ years software engineering experience; 3 5+ years applied ML/GenAI building production systems. Expert with Lang Chain and Lang Graph (tools, agents, state graphs, retries, sub?graphs, observability). Hands?on with Vertex AI (Foundational models, Endpoints, Pipelines, Vector Search, Model Garden; IAM & service architectures). Strong RAG practitioner (chunking strategies, embeddings, hybrid retrieval, rerankers like Cohere/Rerank or bge?rerank, evaluation). Deep experience with vector databases (Pinecone, Weaviate, Milvus, FAISS) and embedding models (OpenAI, Vertex, Cohere, bge?large). Production backends in Python (Fast API) or Node.js, plus React/Next.js front?end experience. Solid cloud experience (Google Cloud Platform preferred; AWS/Azure a plus), Docker/Kubernetes, and CI/CD. Strong understanding of GenAI evaluation (RAGAS, G?Eval, rubric scoring), observability (LangSmith/LlamaIndex observability/Open Telemetry), and prompt/version management. Knowledge of security & governance: PII handling, isolation, data residency, prompt injection defenses, secret management. Excellent communication; proven track record turning ambiguous problem statements into shipped products. Nice to Have Knowledge graphs (RDF/OWL), retrieval planning, and toolformer/agent patterns. LLM serving and routing (DG/mixture?of?experts, function/tool calling, Guardrails, Instructor schemas, Pydantic). LlamaIndex experience; structured RAG (SQL/Graph RAG); function/tool calling integrations (Databases, SaaS).
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