Location: New York, NY / San Francisco, CA / Seattle, WA (Hybrid or Remote Eligible)
Company Stage of Funding: Late-Stage Growth / Series F+
Office Type: Hybrid (NYC 3x/week) or Remote in approved hub cities
Salary: $220,000 – $300,000 + Competitive Equity
Visa: No sponsorship available
Our client is building the world’s largest virtual clinic for women and families, serving over 2,000 employers and health plans globally.
They are becoming an AI-native healthcare organization and are building foundational AI infrastructure that powers critical experiences across their platform — including chatbots, recommendation engines, search, intelligent workflows, and GenAI-powered healthcare experiences.
Backed by top-tier investors including Sequoia, General Catalyst, Dragoneer, and Lux Capital, the company has raised over $425M and is operating at massive scale across fertility, maternity, pediatrics, menopause, and family healthcare.
This is an opportunity to join a foundational AI engineering team where you will directly shape the future of AI-powered healthcare products used by millions of users.
Design, build, and deploy end-to-end AI-powered applications and infrastructure
Build production-grade LLM systems using RAG, agent frameworks, orchestration layers, and modern AI tooling
Develop AI-powered chatbots, recommendation engines, search systems, and intelligent workflows
Own AI/ML product development from 0-to-1, from architecture through production deployment
Design scalable ML pipelines for experimentation, fine-tuning, evaluation, and deployment
Work closely with product, data, analytics, and engineering teams to deliver AI-native product experiences
Build backend systems and APIs supporting AI workloads and inference pipelines
Drive technical architecture and engineering best practices across AI systems
Work with modern AI platforms including OpenAI APIs, Vertex AI, PyTorch, TensorFlow, and agent frameworks
Translate healthcare and user data into intelligent, production-ready AI systems
Contribute to AI platform strategy and help shape the company’s long-term AI roadmap
Operate autonomously in a fast-moving, highly ambiguous AI product environment
Balance rapid iteration with scalability, safety, reliability, and performance
Collaborate cross-functionally with product and business stakeholders to identify impactful AI opportunities
Stay current with emerging LLM, RAG, and agentic AI technologies and integrate them into production systems
6–15 years of experience in software engineering or AI/ML engineering roles
Strong software engineering foundation with backend-heavy product engineering experience
Experience building AI/ML products end-to-end in production environments
Hands-on experience with LLMs, RAG systems, and agent frameworks
Experience shipping production AI products from 0-to-1
Strong Python engineering experience
Experience with chatbot systems, recommendation engines, search, or GenAI applications
Experience working across the full ML lifecycle including ingestion, preprocessing, training, deployment, and monitoring
Strong distributed systems and backend architecture skills
Experience collaborating closely with product and cross-functional teams
Comfortable operating autonomously in fast-moving startup or high-growth environments
Strong builder mentality with high ownership and execution ability
Comfortable writing production-grade code without heavy AI tooling dependence
Ability to explain AI systems and technical tradeoffs clearly to non-technical stakeholders
Experience building production LLM applications at scale
Experience with RAG architectures and retrieval pipelines in production
Experience with AI agent frameworks and orchestration systems
Experience building chatbot, recommendation, or intelligent search systems
Strong backend engineering foundation transitioning into AI/ML
Experience with OpenAI APIs, Vertex AI, LangChain, LlamaIndex, or similar tooling
Healthcare or digital health AI experience
Experience handling high-volume production AI workloads
Experience measuring production AI system performance and reliability
Strong product-minded engineering instincts
Experience working at high-growth product companies
Experience owning projects from architecture through deployment
Experience balancing ML experimentation with production engineering rigor
Strong understanding of distributed systems and scalable infrastructure
Experience working with PyTorch or TensorFlow
Strong coding interview and system design capability
Ability to discuss production metrics, scale, and operational performance of AI systems
Experience building AI features with meaningful user or business impact
Experience working on AI-powered user-facing products instead of purely internal ML infrastructure
Base salary: $220,000 – $300,000
Competitive equity package
Opportunity to help build foundational AI infrastructure at massive scale
Work directly on cutting-edge AI systems impacting millions of healthcare users
Exposure to advanced LLM, RAG, and agentic AI deployment challenges
Strong technical ownership and autonomy
High-growth healthcare AI company trajectory
Backed by Sequoia, General Catalyst, and other top-tier investors
Collaborative, product-focused AI engineering culture
This is an opportunity to join one of the most ambitious AI transformations happening in healthcare today.
You’ll work on foundational AI systems powering healthcare experiences at massive scale while helping define how AI-native healthcare products get built responsibly and effectively.
If you enjoy building production AI systems, shipping 0-to-1 AI products, solving hard engineering problems, and operating at the intersection of backend engineering and modern AI infrastructure, this role offers exceptional scope and impact.
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