Key skills
Software EngineeringAI/ML SystemsLLM APIsPrompt EngineeringTool UseFunction CallingStructured OutputsRAG SystemsEmbeddingsVector StoresRetrieval OptimizationAgent FrameworksAgent OrchestrationFine-tuning SFTFine-tuning RLHFFine-tuning LoRAHealthcare Data HandlingRegulatory Compliance HIPAARegulatory Compliance SOC 2AIMLLLMOpenAIAnthropicRAGCI/CD
About this role
Cadence is building a remote care delivery system that keeps older people healthy, out of the hospital, and at home. The Senior AI Engineer will design and ship production agents that synthesize real-time clinical data and surface proactive care recommendations, ensuring reliability in patient outcomes.
Responsibilities:
- Design, build, and deploy clinical AI agents that reason over patient context, invoke tools, and generate care recommendations
- Own reliability, observability, and cost efficiency of LLM-powered workflows at scale
- Build and optimize RAG pipelines over clinical knowledge bases, treatment protocols, and real-time patient data
- Develop evaluation frameworks: offline benchmarks, safety tests, regression suites, and LLM-as-judge pipelines wired into CI/CD
- Design multi-step agent orchestration: planning, memory, tool use, error recovery, and human-in-the-loop escalation paths
- Collaborate with clinical, product, and engineering teams to translate patient care needs into AI system design
- Stay at the forefront of AI and engineering best practices, continuously pushing the team to raise the bar on quality, performance, and architecture
Requirements:
- Bachelor's or Master's degree in Computer Science, Engineering or related field, or equivalent work experience
- 5+ years of software engineering experience, with 2+ years building AI/ML-powered systems in production
- Hands-on experience with LLM APIs (OpenAI, Anthropic, open-source models) including prompt engineering, tool use / function calling, and structured outputs
- Experience building RAG systems: embeddings, vector stores, retrieval optimization, and grounding
- Experience in a high-growth, fast-paced environment with end-to-end ownership from design through production
- Experience with agent frameworks or orchestration patterns (tool calling, planners, multi-agent coordination)
- Fine-tuning experience (SFT, RLHF, LoRA) on domain-specific tasks
- Healthcare or regulated-industry experience (HIPAA, SOC 2, clinical data handling)