Senior Staff Engineer, Developer Infrastructure

About the Company

Hippocratic AI is a generative AI company focused on healthcare, providing safe, autonomous clinical conversations.

We expect the role to be in our Palo Alto office five days a week, unless otherwise specified.

As a Senior Staff Software Engineer at Hippocratic AI, you’ll define the engineering standards, CI/CD infrastructure, and developer platform that enable a safety‑critical healthcare AI company to ship with confidence. You’ll architect foundational systems that power reliable, testable, and incrementally deployable software across all products and partner deployments, operating at the intersection of software craftsmanship, production engineering discipline, and AI‑first development workflows.

This is a senior individual contributor role in Engineering, reporting to the VP of Engineering. You’ll set direction across the full software delivery lifecycle—testing architecture, build and release pipelines, feature flag strategy, observability, and developer tooling—partnering directly with ML researchers, clinical advisors, and product leaders to turn ambiguous requirements into production systems robust enough for healthcare contexts.

From establishing design patterns that keep a fast‑growing codebase comprehensible and testable by humans, to building deployment infrastructure that enables frequent, safe releases, your work will determine how Hippocratic AI ships software for years to come.

We’re looking for senior staff‑level engineers who have built and scaled software systems across multiple technology generations—a structural problem solver who sets the technical bar and inspires others.

• Define the engineering standards and quality bar across the organization. Set and uphold best practices for code structure, testing architecture, observability, and deployment. Lead by example in code reviews and system design discussions to raise the floor for all engineers.
• Own production readiness end‑to‑end. Build and ship features where testability, observability, incremental deployability, and safe rollback are constraints from day one. Define what "done" means across the engineering org and enforce it without becoming a bottleneck.
• Architect for testability and modularity at scale. Bring structural discipline to a codebase that must grow quickly without rotting. Champion clean interfaces, dependency inversion, and appropriate layering—the design patterns that make complex, AI‑powered production systems comprehensible and testable by humans.
• Own the end‑to‑end CI/CD pipeline and release infrastructure. Design and implement staged rollout strategies—canary deployments, blue/green releases, progressive delivery—to give the team confidence to ship frequently without sacrificing reliability in a clinical environment.
• Establish and steward feature flag and safe deployment practices. Build the infrastructure for gradual rollouts, controlled experimentation, and fast recovery. Make incremental delivery the default across the engineering org, not the exception.
• Multiply developer velocity through systematic tooling improvements. Identify and eliminate friction across the development lifecycle—local environments, test infrastructure, build speeds, linting, and inner‑loop performance. Make the team measurably faster without accumulating new technical debt.
• Operate fluently in an AI‑assisted development environment. Use AI‑powered coding tools, automated test generation, and LLM‑assisted debugging as force multipliers. Help the broader team adopt these workflows thoughtfully—capturing the speed gains while maintaining engineering rigor on a safety‑critical platform.
• Serve as the technical voice across Clinical, ML, and Product. Translate between researchers, clinical advisors, and product managers to turn ambiguous, cross‑functional requirements into robust, maintainable, and safe systems for healthcare contexts.
• Treat patient safety as a first‑class engineering concern. Because our software runs in clinical environments where reliability directly impacts patient outcomes, bring that gravity—not as a constraint on velocity but as a design principle—to…