You will design, build, and deploy end-to-end AI-powered solutions using foundation models like OpenAI and Gemini, applying orchestration techniques such as RAG, multi-call prompting, and agent frameworks. You will work with product, data, and engineering teams to turn rich healthcare data into actionable insights and intelligent workflows. You will develop robust ML pipelines and platform components enabling experimentation, fine-tuning, and production deployment, with a focus on scalability, safety, and performance. You will prototype and productionize AI-driven features like personalization, care routing, decision support, and summarization, drive architecture decisions, mentor engineers and data scientists, and stay current with the evolving LLM landscape.
Responsibilities
- Design, build, and deploy end-to-end AI-powered solutions using AI models and orchestration techniques such as RAG, multi-call prompting, and agent frameworks
- Work with product, data, and engineering teams to turn healthcare data into actionable insights and intelligent workflows
- Develop robust ML pipelines and platform components for model experimentation, fine-tuning, training, and production deployment
- Prototype and productionize AI-driven features such as personalization, care routing, decision support, and summarization
- Drive architecture discussions and technical decision-making across AI/ML systems
- Mentor engineers and data scientists across the organization
- Stay current with the evolving LLM and applied AI landscape
Requirements
- Strong track record building AI-powered applications using foundation models and orchestration techniques (RAG, agents, LangChain, vector search), or deep data science experience across the full lifecycle
- Experience integrating and deploying foundation models via platforms like OpenAI or Google Vertex AI
- Understanding of health-related datasets including user behavior, care journeys, health profiles, and provider interactions
- Fluency in Python and experience with backend or platform engineering in one or more additional languages (Go, Java, etc.)
- Familiarity with cloud-native systems including containerization, orchestration, and distributed systems
- Experience with data preprocessing, feature engineering, model evaluation, and end-to-end ML deployment workflows
- Strong communication skills and collaborative mindset
- Bachelor's or Master's degree in Computer Science or related field, or equivalent experience
- Minimum of 8 years of experience in backend development, platform architecture, and ML/AI platforms or products
Benefits
- Employer-covered health, dental, and insurance plan options
- Maven for Mavens: access to the full platform and specialists including mental health, reproductive health, family planning, and pediatrics care
- Wellness partnerships
- Hybrid work, in-office meals, and work together days
- 16 weeks 100% paid parental leave and new parent stipend (after 1 year)
- Annual professional development stipend and access to a personal career coach
- 401K matching for US-based employees with immediate vesting
- Equity