Applied AI Engineer

About the role

Cadence is building a remote care delivery system designed to keep older people healthy at home, reducing hospital stays and improving patient outcomes. As an Applied AI Engineer, you will design and deploy AI agents that analyze real-time patient data, provide proactive care recommendations, and assist clinicians.

Responsibilities

• Design and build clinical AI agents that reason over patient context, invoke tools, and generate care recommendations.
• Own reliability, observability, and cost efficiency of AI-powered workflows at scale.
• Build and optimize Retrieval-Augmented Generation (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.
• 3+ 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.

Nice to have

• 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).

Qualifications

• Experience with agent architectures from prototype to production in a domain where reliability directly affects patient outcomes.
• Ownership of the full lifecycle of AI-powered clinical workflows: retrieval, reasoning, tool use, evaluation, and safety guardrails.

Skills

• Expertise in LLM APIs (OpenAI, Anthropic, open-source models).
• Experience with RAG systems and embeddings.
• Strong understanding of clinical data and treatment protocols.
• Ability to design and implement multi-step agent orchestration.
• Proficiency in evaluating AI-powered clinical workflows.

Benefits

Autonomy to tackle big, complex problems that matter, an opportunity to improve lives every single day, a chance to shape a category-defining company at scale, medical, dental, and vision insurance, competitive total compensation and meaningful equity, TelaDoc (virtual primary care), national and local discounts powered by TriNet, unlimited PTO and paid holidays, remote equipment setup and home office stipend, paid parental leave, 401K and 401K match, charitable donation match program.

Pay

The base pay for this role typically ranges between $135,000 – $165,000 annual base salary. Total compensation includes base salary and equity. The actual base pay is determined by a variety of factors, including experience, skills, training, and business needs. Compensation may vary based on market location and is subject to change.

Schedule

Remote

Location

Remote