Software Engineer, Full Stack

In Brief

• We’re a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.

• You will work closely with product managers, clinicians, data scientists, and other software engineers to build world-class clinical AI/ML products with direct positive impacts to frontline users within leading enterprise health systems.

Who We Are

Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.

We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.

Read more about our recent publication in Nature Medicine that associates our products with lives saved.

What you’ll do

As a Software Engineer, you will be instrumental in the development and deployment of our clinical AI/ML products within leading enterprise health systems, involving close collaboration with product managers, clinicians, data scientists, and other engineers. Your contributions will be critical for expanding our product offering, directly impacting the company's revenue growth.

Responsibilities

• Full Stack Product Ownership: Design, develop, test, deploy, and maintain robust and scalable full-stack clinical AI modules in production.

• AI-Native Development: Leverage AI coding tools (e.g., Claude Code, Cursor) to rapidly build an end-to-end application in production quality grade and AI agents to optimize testing, debugging, and production maintenance.

• Technical Design and Scoping: Partner with product managers, clinical, data scientists, and other software engineers to integrate our AI insights into intuitive and seamless clinical workflows.

• Product Quality: Develop comprehensive and robust automated end-to-end tests to ensure platform and application functional integrity, meeting the requirements of enterprise health systems and regulatory.

Minimum qualifications

• BS in Computer Science or other relevant technical discipline.

• 3+ years of experience building and maintaining scalable and reliable full stack applications in production using modern front-end technologies (React and Typescript preferred).

• 3+ years experience in developing and deploying end-to-end applications on a cloud platform (AWS preferred) powered by relational databases (e.g., Postgresql, MySQL, etc.) or cloud-based storages.

• Experience with leveraging AI coding tools (e.g., Claude Code, Cursor, Codex) across the design, development, testing, and deployment lifecycle.

• Experience handling ambiguity and uncertainty in a startup.

Preferred qualifications

• Experience shipping AI/ML products in healthcare and/or at startups.

• Experience working cross-functionally with clinicians to align on workflow and product functionality expectations.

• Experience with health data, integration with electronic health records (EHR) systems, and health IT interoperability standards.

Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.