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.