About The Position

We are seeking a senior AI engineer to design and build production-grade LLM-powered applications and agentic systems. This role owns the end-to-end development of intelligent solutions, from architecture to deployment, leveraging Python, modern LLM frameworks, and scalable system design. The position involves developing RAG pipelines over enterprise data, building multi-step tool-using agents, integrating AI systems with APIs, backend services, and cloud platforms, and establishing strategies for evaluation, reliability, and performance.

Requirements

  • 2–3 years of hands-on experience developing agentic workflows.
  • Strong Python expertise and experience building and deploying production-grade backend systems.
  • Hands-on experience developing applications using LLMs, including prompt engineering and orchestration.
  • Proven experience with RAG architectures, embeddings, and vector databases.
  • Experience with agentic frameworks such as LangChain, LangGraph, or AutoGen.
  • Strong system design skills and experience building and scaling cloud-based applications.

Nice To Haves

  • Experience working in the healthcare insurance payer space or payer-domain knowledge.
  • Candidates able to work onsite three days per week are preferred, though fully remote candidates are also considered.

Responsibilities

  • Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python.
  • Design and implement RAG pipelines over enterprise data using embeddings and vector databases.
  • Build multi-step, tool-using agents with planning, execution, and memory using frameworks such as LangChain.
  • Integrate AI systems with APIs, backend services, and cloud platforms.
  • Establish evaluation, reliability, and performance strategies for accuracy, latency, and cost.
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