About this role

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

BS/MS in Computer Science, Machine Learning, or related field.
3–5 years of AI/ML engineering; minimum 2 years building LLM-powered systems shipped to production.
Strong Python; PyTorch or Hugging Face Transformers; AWS or GCP; Docker/Kubernetes.
Portfolio of shipped AI work required — agentic pipelines, RAG systems, or fine-tuned models.
No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship.

AI/ML Engineer

Key skills