Top Tech Jobs & Startup Jobs in Austin, TX

Leads and mentors Applied Scientists developing, evaluating, and deploying machine learning and language-model solutions for healthcare workflows. Translates clinical and business problems into scalable AI systems, applies rigorous statistical methods and experimentation, partners with engineering and cross-functional stakeholders, and ensures models are reliable, reproducible, and safe. The role also contributes hands-on technical work, recruiting, onboarding, and team development.

Leads healthcare analytics projects using clinical, claims, pharmacy, and eligibility data to evaluate cost, utilization, quality, and program performance. Develops statistical analyses, predictive models, dashboards, and reporting solutions; identifies optimization opportunities; partners with clinical, product, engineering, and business teams; presents recommendations to stakeholders; and mentors junior analysts.

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Leads a 20-plus-person distributed Review Engineering organization across three agile squads. Owns technical direction, production reliability, incident response, system scalability, delivery metrics, hiring, performance management, and engineering career growth. Partners with Product, Design, Security, Clinical Operations, and peer engineering teams to deliver reliable, secure, high-quality systems in a regulated healthcare environment.

Lead end-to-end technical integrations with enterprise healthcare customers from pre-sales through production. Scope and deliver architecture, POCs, API integrations, data mappings, and runbooks. Ensure AI/ML features meet regulatory and clinical safety standards, build reusable integration patterns, collaborate cross-functionally, and mentor junior engineers to drive successful go-lives.

Lead design and development of scalable, cloud-native AI healthcare payment integrity platforms. Provide technical leadership, own production code and releases, design data/retrieval architectures, ensure observability, security, and compliance, and collaborate with ML, product, and architecture teams to deliver performant SaaS solutions.

Lead technical design, build, and operate scalable, secure healthcare integration systems. Drive architecture, event-driven distributed systems, APIs, observability, IaC, CI/CD, incident response, cross-functional delivery, and mentor engineering teams.