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Salary: USD 150,000 - 250,000 / annual
Cadence is a clinical AI company automating chronic disease treatment. The company has partnered with 20+ leading health systems, integrated deeply with EMR systems, and serves a population of 100,000+ patients. Cadence was recognized by TIME as a Top 100 HealthTech Company and by LinkedIn as a Top Startup (#4, 2025).
As an AI Engineer, you will design and ship production agents that synthesize real-time clinical data, surface proactive care recommendations, and take action on behalf of clinicians. You'll own the full lifecycle of AI-powered clinical workflows where reliability directly affects patient outcomes.
Key responsibilities include:
- 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 integrated into CI/CD
- Design multi-step agent orchestration including planning, memory, tool use, error recovery, and human-in-the-loop escalation
- Collaborate with clinical, product, and engineering teams to translate patient care needs into AI system design
- Stay current with AI and engineering best practices, continuously raising the bar on quality, performance, and architecture
Required qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related field (or equivalent work experience)
- 2+ years building AI/ML-powered systems in production
- Experience in high-growth, fast-paced environments with end-to-end ownership from design through 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
Preferred qualifications:
- 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)
