Sidecar Health is redefining health insurance with a mission to make excellent healthcare affordable and accessible for everyone. The Senior AI Engineer will design, architect, and deploy AI-powered systems that enhance member experiences and operational efficiency, taking full ownership from design to deployment.
Responsibilities:
- Design, architect, and deploy AI-powered systems that directly impact member experience and operational efficiency
- Build and optimize LLM-driven applications using advanced prompt engineering, RAG architectures, and agentic workflows
- Design scalable AI pipelines using modern orchestration frameworks (LangChain, LangSmith, LlamaIndex, etc.)
- Architect multi-agent systems capable of reasoning, planning, and executing complex multi-step tasks
- Implement evaluation and monitoring frameworks to measure AI performance, detect hallucinations, and ensure reliability at scale
- Own cloud-native AI infrastructure for performance, scalability, cost efficiency, and security
- Partner with Product and Engineering leadership to identify and execute high-impact AI initiatives
- Stay at the frontier of the AI ecosystem and translate emerging capabilities into production-ready systems
- Establish internal standards, tooling, and best practices for AI development across the organization
Requirements:
- Bachelor's or Master's degree in Computer Science, Information Systems, Business Administration, or a related field
- 5+ years of professional software engineering experience, including meaningful ownership of production systems
- Significant hands-on experience building and deploying AI/ML systems in production
- Strong proficiency in Python and TypeScript (Next.js a plus)
- Deep experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock) and orchestration frameworks (LangChain, LangSmith, LlamaIndex)
- Strong understanding of advanced prompt engineering techniques and LLM optimization strategies
- Experience designing and deploying RAG systems, vector databases, and semantic search applications
- Cloud infrastructure expertise (AWS preferred): Lambda, Step Functions, API Gateway, DynamoDB, S3
- Strong understanding of LLM behavior: tokenization, embeddings, context limits, evaluation, and hallucination mitigation
- Demonstrated track record of shipping scalable, production-grade AI systems — not prototypes or demos
- MUST BE BASED IN CALIFORNIA
- Experience with infrastructure as code (AWS CDK, SAM, Terraform)
- Experience in healthcare, insurance, or regulated environments
- Experience fine-tuning models or building custom model pipelines
- Familiarity with observability tools (DataDog, CloudWatch, LangSmith)
- Contributions to open-source AI projects or published technical work