Salary
💰 $184,100 - $216,600 per year
Tech Stack
AWSCloudGoogle Cloud PlatformMongoDBPythonTypeScript
About the role
- Design, deploy, and scale generative AI solutions that directly impact patient care
- Collaborate closely with Product, Data Engineering, and Application Engineering teams to integrate AI into the platform
- Own the full lifecycle of GenAI solutions: prototyping, building scalable data pipelines, developing, testing, and ensuring high quality
- Deploy production-ready GenAI solutions and monitor their performance for robustness, cost-effectiveness, and compliance with privacy and regulatory standards
- Balance innovation with operational excellence: experiment with new approaches while ensuring deployed solutions are robust
- Build early prototypes to deliver AI features into production and expand AI impact across the organization
- Create reusable frameworks, optimize performance, and identify opportunities to enhance the platform and patient outcomes
- Lead efforts to bring next-generation AI capabilities to mental health care, transforming therapy experiences for providers and patients alike
Requirements
- 8+ years in software engineering, data engineering, or platform engineering/infra
- 5+ years of experience with Python
- 7+ Experience with Public Cloud (AWS, GCP, etc.)
- 5+ years of experience deploying and managing software configuration, build, and deployment processes (CI/CD pipelines) and associated tools
- 1+ years of experience with building production-ready, AI-powered products at scale to include hands-on experience with foundational AI models (OpenAI, Anthropic, AWS Bedrock), orchestration and safety frameworks (Langchain, Llamaindex), and vector databases (Pinecone, MongoDB, Milvus)
- Experience collaborating with Data Engineering teams to build scalable data pipelines
- Strong and effective communicator
- Familiarity with Typescript (preferred)
- Experience working in Healthcare or other regulated environments (preferred)
- Familiarity with even-driven architectures (preferred)
- Experience contributing to early-stage team growth (0 → 1) (preferred)
- Eligible to work in the United States / US-based only