Build and maintain production-grade LLM pipelines and agentic workflows.
Design and optimize RAG architectures with vector databases (Pinecone, FAISS, Weaviate) at scale.
Implement agentic systems using LangGraph/LlamaIndex for tool use and coordination.
Own prompt engineering, model versioning, evaluation (RAGAS/DeepEval), and LLMOps instrumentation.
Integrate AI features into large-scale data pipelines with observability and guardrails.

🎯 Requirements

BS/MS in Computer Science, Machine Learning, or related field.
3–5 years AI/ML engineering; at least 2 years building LLM-powered systems in production.
Strong Python; PyTorch or Transformers; AWS or GCP; Docker/Kubernetes.
Portfolio of shipped AI work: agentic pipelines, RAG systems, or fine-tuned models.
No visa sponsorship. Authorized to work in the US without sponsorship.

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