AI Solutions Engineer

About Knit Health Knit Health is building a novel clinical foundation model to improve the way healthcare is delivered. We combine expertise in AI with deep clinical knowledge to develop safe, trustworthy systems that improve care, expand access, and reduce waste. Knit is led by a founding team from the University of California Berkeley who have developed a novel AI architecture which learns to reason like physicians. We’re now closing the loop and using our novel foundation model, together with frontier clinical LLMs, to build a next generation clinical intelligence platform for providers. We are venture backed and have partnered with multiple US-based health systems and data providers. What you'll do Knit Health is seeking an experienced back-end engineer to adapt our AI technology to customer-specific needs. You’ll work closely with our health system clients and internal product and AI teams to understand how our foundational models can best improve patient outcomes and clinician efficiency, and then design and implement data flows, APIs, and other back-end systems to execute on that vision. In this role, your primary mission will be to extend the reach of our models into new care settings and therapeutic contexts. As a foundational member of our engineering team, you will work closely with our AI researchers to shape both immediate and long-term technical capabilities, directly influencing how our technology safely and effectively integrates into the care delivery models of the future. Solutions Design & Client Integration Deepen Client Technical Partnerships: Collaborate directly with health system partners to audit their clinical workflows and technical ecosystems, ensuring our integration strategies align with their specific EHR environments and capabilities. Design Seamless Data Exchanges: co-design and implement robust API layers to ingest clinical data and deliver model-derived insights back into client-facing systems, whether through custom-built endpoints or the orchestration of existing vendor APIs. Data Transformation & Mapping: Own the end-to-end data translation process, building flexible transformation layers that normalize disparate clinical schemas (EHR, claims, etc.). Product Engineering & Logic Layer Build Intelligence Wrappers: Develop the critical business logic (primarily in Python, SQL) that sits atop our core AI models—designing the constraints, validations, and enhancements that ensure model outputs are clinically safe, contextually relevant, and actionable. Scale High-Performance Systems: Design and maintain the back-end infrastructure required to support real-time and batch-processing pipelines, ensuring high availability and low latency as we scale to new therapeutic contexts. Observability & Strategic Collaboration Engineer System Reliability: Establish comprehensive monitoring, observability, and debugging frameworks to proactively identify and resolve performance bottlenecks, data drift, or other defects within our production environments. Influence the AI Research Agenda: Act as the primary bridge between the field and our AI research team, translating real-world implementation challenges into core engineering requirements that shape the long-term capabilities of our foundational models. Minimum qualifications 3+ years of experience in backend or full-stack development. Proficiency in Python and SQL. 2+ years of experience designing and developing APIs for ease-of-use, maintainability, and observability. Experience with concurrency, asynchronous patterns, and event-driven architectures. Knowledge of data modeling fundamentals. Familiarity with cloud platforms (Azure, AWS, or GCP), containerization, and deployment pipelines. Experience writing automated tests and testing best practices, including mocking and dependency injection. Strong communication skills with the ability to understand and translate complex analytical data and technical analyses for diverse audiences. Nice-to-haves Familiarity with healthcare (clinical and administrative) workflows. Familiarity with Epic, Cerner, or other electronic health record systems. Experience with FHIR, X12, and other healthcare data standards; experiencing handling HIPAA-covered data and associated compliance issues. Experience building LLMs and/or integrating LLMs technically with back end products. Although this role involves backend work only, familiarity with Javascript, Typescript, and front-end frameworks is a plus. Prior work in a startup or high-growth environment. Salary Range Knit Health offers a competitive compensation package that includes base salary, equity, and opportunities for advancement. The starting salary range for the AI Solutions Engineer is approximately $135,000 to $165,000 per year. Benefits Generous benefits for full-time employees include: medical, dental, and vision coverage with 100% of premiums paid for employees and dependents (full coverage for dental, vision, and our Gold medical plan; employees may choose to buy up to Platinum); coverage begins on the first day of employment. Additional benefits include a 401(k) plan and 24 days of PTO annually. Final Notes Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. Knit Health is an equal opportunity employer and is committed to a diverse workplace. People from diverse racial, ethnic and cultural backgrounds, women, LGBTQ+ individuals, and persons with disabilities are highly encouraged to apply.