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Lead Data & Integrations Engineering to enhance healthcare integration and data platforms. Manage delivery processes, team development, operational excellence, and cross-functional partnerships.

Lead technical integrations of Cedar's platform with client healthcare systems: discover requirements, map data formats, validate data/UAT, communicate technical security and authentication needs, manage complex projects, and represent customer needs to engineering and product teams.

The Solutions Architect leads client integration of Cedar's platform, ensuring successful project delivery through client communication and technical expertise while managing complex data structures and operational workflows.

Lead revenue-cycle performance analyses, diagnose root causes, quantify value (ROI/collections lift), and translate findings into pragmatic, stakeholder-ready recommendations. Partner cross-functionally to scope analyses, validate data, and drive strategic workstreams that inform product roadmap and client outcomes.

The software engineer will build full-stack features for Kora's voice AI agent, integrating data, refining prompts, and expanding multi-modal capabilities while mentoring peers and ensuring technical quality.

Build developer-facing security services and tools, partner with engineering teams through the SSDLC to threat model and review code, and contribute to security automation (static analysis, vulnerability management, asset inventory) to help Cedar scale secure patient-facing products.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Senior Director of Client Management will drive client strategy, build relationships with executive partners, and collaborate with internal teams to enhance client engagement and drive partnership success in the healthcare tech industry.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

Lead the design and execution of a new enterprise data platform, ensuring metrics reliability and supporting AI-driven products, while mentoring engineers and collaborating across teams.