Top Tech Jobs & Startup Jobs in Chicago, IL

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.

Embed with Finance to design, build, and operate production AI systems that integrate with ERP and data platforms, enable conversational and retrieval-based workflows, automate financial quality controls, surface operational intelligence, and support executive reporting. Own end-to-end delivery from discovery through deployment, monitoring, evaluation, and enablement while ensuring governance, compliance, and stakeholder adoption.

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 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.

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.