Jobs at Omada Health

Lead design and implementation of scalable backend systems that ingest, process, and serve high-volume health data. Own projects end-to-end, drive integrations with third-party APIs, improve data reliability and observability, mentor engineers, and partner with product, clinical, and data teams to deliver clinically meaningful insights.

Lead the technical development and automation of enrollment forecasting models, collaborating with various departments to enhance decision-making and forecast accuracy.

Lead enablement strategy and scalable operations for Customer Success Managers, translating customer and field feedback into roadmaps, resources, AI-enabled workflows, and self-serve tools. Partner cross-functionally to prioritize work that improves customer conversations, retention, and growth while modernizing knowledge management, communications, and intake systems to reduce manual work and increase team efficiency.

Lead national new business growth for enterprise employer segments at Omada Health, focusing on achieving revenue goals and strategic alignment across departments.

Design and build AI-augmented test tooling and automated test infrastructure across mobile, web, and backend. Integrate testing into engineers' workflows (IDE, CI, monitoring, chatops), define quality gates, instrument AI usage and costs, ensure secure handling of PHI, and produce reusable libraries, documentation, and training to help teams adopt automated quality workflows.

Lead cross-functional Engineering, Product, and Design execution for large, complex initiatives. Own integrated launch planning, risk and dependency management, metrics/OKRs, stakeholder alignment, and program rituals to ensure disciplined delivery and measurable business/member impact.

Lead design of AI-supported member and care experiences, defining interaction models, prototyping AI-driven flows, and designing service blueprints. Partner with product, engineering, data, clinical, and research teams to translate AI capabilities into trustworthy, clinically appropriate, and scalable experiences. Create prototypes, design artifacts, evaluation loops, and influence senior stakeholders to align user needs, business goals, and technical constraints.

Lead Omada's investor relations and capital markets strategy as a public company: craft and communicate the equity story, engage investors and analysts, manage earnings and disclosure processes, analyze investor models and ownership trends, and partner with Finance, Legal, and executives on guidance, investor targeting, and capital-markets activities.

Lead end-to-end product design for Omada’s care programs: define problems, create concepts and rapid prototypes, validate with research, and ship consumer-grade mobile (iOS/Android) experiences. Partner with product, engineering, clinical, and data teams, contribute to design systems, and design AI-powered features using AI tools as part of the workflow.

Part-time Director-level HR Business Partner supporting Commercial, Corporate Strategy & Ops, and Finance. Leads organizational design, workforce and capability planning, change leadership, and leadership coaching. Uses AI fluency and people data to inform strategy, redesign roles for human-AI collaboration, streamline HRBP workflows, and measure P&C impact. Partners with centers of excellence and employee relations; advises on complex people issues. Requires travel up to ~25-30% and work during core PST business hours.

As Chief Revenue Officer, lead Omada Health's commercial strategy to drive growth, market access, and integration of AI in operations, ensuring sustainable success across healthcare channels.

Lead backend-focused engineering to design and ship member- and care team-facing experiences. Own architecture end-to-end, set technical direction and quality standards, mentor engineers, and deliver scalable, secure APIs with CI/CD, cloud deployments, and GenAI/LLM-informed workflows.

Lead design and implementation of scalable, production-grade data products and feature pipelines for ML. Build batch and streaming pipelines, ensure data quality, observability, and reproducibility, partner with data scientists and platform teams, and drive cross-team architecture and standards for ML-ready datasets.

Lead design, deployment, and monitoring of LLM-based AI solutions. Build end-to-end generative AI applications, fine-tune models, integrate LLM APIs into products, ensure post-deployment performance, and collaborate cross-functionally within an Agile environment to drive measurable business impact in healthcare.

The Senior Software Engineer at Omada Health will develop scalable backend systems for healthcare applications, lead projects, code, and mentor junior engineers while integrating AI tools and collaborating across teams.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

Design, build, and operate scalable data and AI platform capabilities. Create reusable abstractions, templates, and services for data pipelines and products. Integrate Generative AI for discovery and automation, ensure data quality, lineage, observability, security, and support cross-functional analytics and applied-AI teams.

Design, build, and maintain scalable, secure data architectures, models, and ETL pipelines. Integrate diverse data sources, optimize performance and data quality, implement governance, monitor production SLAs, and collaborate with data scientists, analysts, and product teams. Provide technical leadership, documentation, and training to improve engineering practices across the organization.

Lead and grow a Data Engineering organization to design, build, and operate scalable, governed data pipelines and enterprise data products. Define technical strategy and roadmap, improve data quality, reliability, observability and governance, partner with cross-functional teams, and drive platform evolution to enable analytics, ML, reporting, and self-service insights.

Lead research and development of longitudinal health trajectory models and next-best-action decision algorithms. Translate member data into deployable, clinically meaningful models, set evaluation standards, mentor scientists, and collaborate with product, engineering, and clinical teams to productionize and monitor ML solutions that optimize interventions and health outcomes.