Lead Clinical Automation & AI Systems Engineer

• 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

• About Generation Next Fertility (GNF)
• 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.

• The Mission
• 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.

• What You’ll Build & Own
• 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 LangGraph) 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 Roadmapping: Embed with clinical coordinators, billing specialists, and fertility doctors to reverse-engineer messy, manual workflows and convert them into clean, high-scale software systems.

• What You Bring
• Core Software & Engineering Foundations:
• 3–5+ years of professional software development experience (proficient in Python and/or modern TypeScript).
• 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 ( LangGraph, LlamaIndex, CrewAI, AutoGen ) 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, LangSmith, Arize Phoenix, DeepEval).
• 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 morning, and sit elbow-to-elbow with a clinical coordinator or fertility physician in the afternoon to map their workflow.
• Product Ownership: Comfortable operating in a fast-paced environment where you own the full lifecycle from problem discovery through implementation, unit testing, user training, and maintenance.

• Nice-to-Haves
• Healthcare interoperability: Experience with healthcare standards and APIs such as FHIR, HL7, or SMART on FHIR is a plus.
• Direct domain experience in fertility care, reproductive endocrinology, ambulatory care, or health-tech startups.
• Experience building custom internal front-ends (Retool, Streamlit, React, or Next.js) for internal human-review interfaces.
• Track record of successfully replacing legacy RPA (UiPath, Power Automate) with clean, maintainable code-based microservices.

• Why GNF?
• Massive Leverage: You will not be a minor cog in an IT department. You will be building the core nervous system of an elite fertility practice, with leadership access directly to founders and clinical heads.
• Tangible Real-World Impact: Fertility is deeply emotional and time-critical. The systems you build directly lower cycle stress for intended parents and stop clinical staff burnout.
• Modern Tech Freedom: We don't want band-aids. You have the mandate and budget to implement modern, state-of-the-art tools and AI architectures without enterprise red tape.
• Comprehensive Benefits: Competitive salary, bonus, health insurance, 401(k) matching, and work flexibility.