AI/ML Engineer

Role Overview: We are seeking a highly skilled AI/ML
Engineer to lead the development, scaling, and productionization of our
advanced AI Agent ecosystem. In this role, you will be responsible for
orchestrating multi -agent LLM systems and developing machine learning models to
analyze complex clinical data for our maternal -care platform.

You will directly oversee and mature three critical
intelligent agents: Agent 1 production billing reconciliation and payer
eligibility), Agent 2 navigation automation), and Agent 3 clinical
pattern recognition executing against an 11K+ escalation corpus).

Key Responsibilities:

• Agent
  Orchestration: Design, build, and optimize multi -agent workflows using
  TypeScript/Node.js to call enterprise LLM APIs.
  
• ML
  Pattern Recognition: Develop and train specialized Python -based
  machine learning pipelines to ingest and detect anomalies, trends, and
  risk indicators within an 11K+ clinical escalation corpus.
  
• Agent
  Lifecycle Management: Maintain and iteratively improve Agent 1 (cross -reconciliation across PCM/BHI/RPM/CCM), advance Agent 2 through its deployment phases, and mature Agent 3 from build
  to production readiness.
  
• Data
  Pipeline Integration: Work closely with the data engineering team to
  process structured and unstructured data via Snowflake (Snowpark /
  Python APIs) and ensure data compliance with HIPAA standards for
  handling Protected Health Information (PHI).
  
• System
  Performance & Evaluation: Establish strict evaluation frameworks
  (evals) for LLM outputs to guarantee clinical safety, accuracy, and
  mitigation of hallucinations in triage recommendation queues.
  

Requirements

Required Technical Skills & Qualifications:

• Languages: Advanced proficiency in Python (for ML data science workloads) and TypeScript
  / Node.js (for backend orchestration and API integration).
  
• AI/LLM
  Frameworks: Strong experience with LLM orchestration frameworks (e.g.,
  LangChain, LlamaIndex, or LangGraph) and commercial/open -source LLM APIs.
  
• Machine
  Learning NLP: Deep understanding of Natural Language Processing (NLP),
  text embedding generation, vector databases, and pattern -recognition
  techniques applied to unstructured text datasets.
  
• Data
  Stack: Hands -on experience with Snowflake and Snowpark using Python APIs.
  
• Healthcare
  Domain (Highly Preferred): Familiarity with US healthcare compliance,
  HIPAA data privacy requirements, and navigating clinical nomenclature.