Top Tech Jobs & Startup Jobs in Seattle, WA

Own Prompt's API and EHR integration roadmap, manage interoperability with major EHRs and Kno2, lead Patient Portal development, guide DevOps priorities, ensure CEHRT/CMS/HIPAA compliance, and coordinate cross-functional product, engineering, sales, and partner initiatives.

Manage and grow a book of SMB and mid-market SaaS accounts by identifying upsell and cross-sell opportunities, building relationships with decision-makers, presenting product value, conducting business reviews, forecasting pipeline, and collaborating with Client Success, Sales, and Product to drive revenue expansion and ensure account health.

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.

Support Engineer will troubleshoot issues in SaaS products, work with engineering and client teams, debug complex API integrations, and write technical specifications. Experience in customer-facing roles and database management is required.

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.