Lead Clinical Automation & AI Systems Engineer

New York, NY

Lead Clinical Automation & AI Systems Engineer
Department: Clinical Operations & Technology Engineering
Reports to: Founders & Associate Director of Clinical Operations
Location: Midtown Manhattan, NYC (Hybrid preferred; Remote considered for exceptional candidates)

Salary: 150-200k yearly

Generation Next Fertility (GNF) is a premier, physician-led reproductive care practice. Fertility treatments (IVF, egg freezing, embryo transfers, pre-conception testing) require deeply complex, high-touch workflows spanning clinical decision-making, real-time lab orchestration, insurance pre-authorizations, and compassionate patient communication.
We believe the future of clinical excellence lies at the intersection of empathetic care and agentic software infrastructure . We are hiring a Lead Clinical Automation & AI Systems Engineer to own the technical architecture that reduces operational friction, unburdens clinical teams, and builds the next generation of automated clinical workflows.

You will design, build, edit, and deploy the internal software and agentic workflows that power GNF. This role goes far beyond simple RPA scripts or Zapier zaps: you will architect resilient, event-driven pipelines where autonomous AI agents augment human expertise — handling everything from automated patient chart preparation and cycle intake to real-time prior-authorization processing and care coordination.

• Autonomous & Assistive Clinical Agents: Design, test, and deploy multi-agent systems that autonomously execute multi-step operational tasks (e.g., insurance verification, medication schedule reconciliation, lab result triaging, and patient-tailored educational updates).
• Stateful Workflow Orchestration: Build resilient, state-driven workflow pipelines (using modern orchestration platforms like Temporal, Inngest, or Lang Graph) that safely bridge probabilistic LLM outputs with deterministic clinical operations.
• Human-in-the-Loop (HITL) Architectures: Architect internal tooling and queues that allow physicians, embryologists, and patient coordinators to supervise, inspect, and approve AI-generated actions before they write back to production systems.
• EHR & Systems Interoperability: Build reliable API-level integrations connecting our core Electronic Health Record (EHR) / IVF Practice Management Systems (eIVF) with our communications stack, billing engines, and laboratory data layers.
• Reliability, Evals & Guardrails: Implement programmatic validation layers (e.g., Pydantic, Instructor), safety guardrails, and automated evaluation suites to continuously measure model latency, hallucination rate, token cost, and clinical accuracy.
• Operational Discovery & Technical Road mapping: Embed with clinical coordinators, billing specialists, and fertility doctors to reverse-engineer messy, manual workflows and convert them into clean, high-scale software systems.

• Core Software & Engineering Foundations: 3–5+ years of professional software development experience (proficient in Python and/or modern Type Script). Solid understanding of API architecture (REST, webhooks, GraphQL) , event-driven systems, and modern relational databases (PostgreSQL/SQL).
• Healthcare workflows & PHI: Demonstrated knowledge of healthcare workflows and safeguards for protected health information (PHI), including HIPAA/HITECH requirements, is required. Hands-on professional experience working in a healthcare setting and handling PHI is also required.
• Applied AI & Automation Tooling:
  • Agentic Frameworks: Hands-on experience building with modern LLM orchestration frameworks (
    Lang Graph, Llama Index, CrewAI, Auto Gen ) and stateful workflow engines (
    Temporal, Inngest, or AWS Step Functions ).
  • Deterministic AI Engineering: Deep knowledge of tool-calling / function-calling , structured data extraction (Pydantic, Instructor, Outlines), and Retrieval-Augmented Generation (RAG) over clinical or operational SOPs.
  • Model Monitoring & Evaluation: Familiarity with tracing, evals, and observability tools (e.g., Langfuse, Lang Smith, Arize Phoenix, Deep Eval).
• Mindset & Problem Solving:
  • Pragmatism Over Hype: You recognize when a problem calls for an autonomous agent vs. a fast deterministic Python script vs. a vendor SaaS tool. You optimize for uptime, clinical safety, and user adoption.
  • Cross-Functional Fluency: You can speak technical details with software vendors in the…