AI Engineer

Responsibilities

• Design, build, and maintain agentic systems and LLM-powered applications to automate healthcare workflows
• Orchestrate agents using LLM APIs (OpenAI, Anthropic) and frameworks like LangChain, LangGraph, or CrewAI
• Develop prompt libraries, agent instructions, and reusable skills to improve accuracy and reliability
• Build validation and confidence-scoring layers to flag low-confidence decisions for human review
• Implement rigorous evaluation and QA frameworks, including golden datasets and hallucination detection
• Establish observability and regression testing frameworks for decision tracing and performance tracking
• Collaborate with data engineering to integrate agent outputs into existing data architectures
• Ensure compliance with healthcare regulations such as HIPAA and FDA guidance
• Document agent architectures, prompt strategies, and best practices

Requirements

• 3+ years of professional experience in data engineering, backend engineering, or machine learning
• 1+ years of hands-on experience architecting agentic systems with LLM APIs and orchestration frameworks
• Strong proficiency in Python and SQL
• Experience with cloud data platforms like AWS or Databricks
• Solid understanding of data modeling, ETL/ELT patterns, and medallion architecture
• Experience building and consuming APIs
• Demonstrated experience with prompt engineering and validating LLM outputs
• Ability to design evaluation frameworks and track performance metrics like precision, recall, and hallucination rates

Preferred Qualifications

• Experience with dbt or orchestration tools like Airflow
• Familiarity with observability tooling such as LangSmith or Langfuse
• Background in healthcare or other highly regulated domains
• Hands-on experience with RAG (retrieval-augmented generation)
• Familiarity with healthcare data standards like FHIR or HL7
• Experience in a startup or high-growth environment