Top Tech Jobs & Startup Jobs in Austin, TX

Manage EDI and enrollment support within the Client Success team, providing hands-on helpdesk triage, client-facing onboarding support, process optimization, knowledge base development, EDI engineering ticketing, and auditing workflows for AI automation opportunities to scale EDI operations.

Lead end-to-end product design for complex health-tech features, conduct user research and testing, define design patterns and systems, mentor mid-level designers, partner with product and engineering on goals and metrics, and use AI tools to accelerate design while prioritizing user-centered solutions.

The RCM Client Success Manager is responsible for managing client relationships post-onboarding, ensuring client satisfaction in clinical, administrative, and billing workflows while identifying growth opportunities within revenue cycle management.

The Associate Client Success Manager will build client relationships, ensure product usage, provide support, and contribute to onboarding and training for rehab therapy teams.

The Accounts Receivable Specialist manages billing and collections for medical services, ensuring compliance and prompt payment from insurance and patients, while resolving claim issues.

The Senior Data Engineer will design and develop data systems and pipelines, perform analyses, and collaborate with stakeholders to improve decision-making in healthcare.

The Senior Full Stack Software Engineer will oversee technical development in a B2B SaaS healthcare environment, mentor junior engineers, and lead product features.

The Payment Posting and AR Specialist will post and reconcile insurance and patient payments, resolve errors, and manage Accounts Receivable tasks while maintaining accurate ledgers.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.