Sidecar Health - Senior Software Engineer
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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 • 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 • 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 • The Reality • This is a startup. We move fast. We prioritize impact over polish. We expect: • Bias for action — ship, learn, iterate • Ownership — you design it, build it, run it • Pragmatism — solve real problems, not theoretical ones • Resilience — ambiguity comes with the territory • Healthcare is complex and broken. The work matters. • What You'll Get • What You'll Get • Competitive salary, bonus opportunity, and equity package • Comprehensive Medical, Dental, and Vision benefits • A 401k retirement plan • Paid vacation and company holidays • Opportunity to make an impact at a rapidly growing mission-driven company transforming healthcare in the U.S.
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
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