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Sakura Health is hiring an early software engineer in the San Mateo office to help turn practice workflows into dependable software. You will work closely with our founders to decide what to build, own deployment, and shape the architecture as we scale.
You will contribute across the stack, build Python services, and collaborate with clinical teams to ensure reliability in real-world use. The role requires 2+ years of production experience and strong Python backend skills.
US healthcare spends well over $1 trillion a year on administration. We are building AI agents that take on that work from start to finish, across scheduling, referrals, eligibility, prior auth, revenue cycle, and more.
Our ambition is bigger than automating individual tasks. We want to build the operating layer that lets healthcare organizations run with dramatically less administrative overhead.
We are still early. Healthcare is only beginning to adopt AI for core operations. Join a small team from MIT, Harvard, and IIT building what we believe will become a fundamental part of how healthcare gets work done.
Our team came out of MIT research labs, quant funds, big tech, consulting, and early-stage companies. We keep the team small and the hiring bar high.
We don't hand off problems. We own them.
Everyone at Sakura is expected to understand the problem, make decisions, and drive work all the way to a real-world result. Scope matters less than impact.
We don't hand off problems. We own them.
Everyone at Sakura is expected to understand the problem, make decisions, and drive work all the way to a real-world result. Scope matters less than impact.
Healthcare has waited long enough.
We move quickly, make decisions with incomplete information, and put working products in front of users early. Speed doesn't mean lowering the bar. It means shortening the path to learning.
The best answers aren't found in a conference room.
We listen to calls, watch workflows, talk directly to operators, and dig into the messy details of how healthcare actually works. Everyone is expected to understand the people and systems we're building for.
We care deeply about the quality of the work, not who gets credit.
We challenge each other directly, change our minds when the evidence changes, and expect exceptional work from ourselves and each other.
A demo working isn't the same as healthcare working.
Our agents have to operate across legacy systems, payer portals, phone trees, faxes, edge cases, and high-stakes workflows. We value reliability and craft as much as cleverness.
Full time
Hybrid
Sakura Health builds AI agents that run front- and back-office operations for specialty practices. A referral arrives, an agent processes it; a payer needs a call, an agent makes it. Our agents work inside existing EHRs, phone systems, fax queues, and payer portals so staff can review completed work and spend more time on patients.
Our agents are running in production inside live practices across senior care, gastroenterology, and cardiology, with a growing set of customer deployments and channel partnerships underway. We are now building the commercial motion to scale them. We raised our seed round from Lightspeed, alongside angels from OpenAI, Sierra, Iterative Health, and Innovaccer.
You will join Sakura as an early engineer, working closely with our technical founders to turn practice workflows into dependable software. You will help decide what to build, own it through deployment and customer use, and shape the architecture and engineering practices future hires will inherit.
A referral may arrive incomplete, a payer portal may change, or an agent may need a staff member to resolve an exception. You will work directly with practice teams to understand these problems and build solutions that hold up in everyday use.
Own reliable delivery. Build Python services and APIs, deployment pipelines, and infrastructure as code. Use Docker with Kubernetes or ECS, with monitoring and alerting to diagnose failures and support growing usage.
Protect sensitive data. Implement encryption, access controls, and audit trails for protected health information and agent actions. Make security decisions explicit and support healthcare compliance requirements.
Shape the product. Spend time with clinic teams, identify where work stalls, and help the founders prioritize what to build. Ship focused improvements, observe how staff use them, and refine the product based on what works.
Set the engineering standard. Shape service boundaries, data models, code review, testing, and observability. Leave clear documentation so the next engineer can understand and extend what you build.
You enjoy turning an unclear customer problem into working software. You can scope a useful first version, explain your tradeoffs, and follow through when something breaks after launch.
2+ years of professional software engineering experience, including taking a system from an initial idea into production and supporting it as usage grows.
Strong Python backend skills across APIs, data processing, and service reliability. You can investigate a failure and follow it through to a durable fix.
Comfort building across the stack, from data models and backend services to the interfaces staff use and integrations with external systems.
Practical judgment about security, including the additional risks of software that can take actions on a user’s behalf.
Sound product and engineering judgment. You choose simple approaches, adapt as requirements change, and know which safeguards must be in place before shipping.
Clear communication and a collaborative approach. You document decisions, ask for feedback, and help teammates understand unfamiliar parts of the system.
Willingness to spend regular time onsite at partner clinics and hospitals to understand workflows and support deployments.
First 30 days: Learn a practice workflow and the codebase, trace how data moves through the system, and ship a focused improvement with the founders.
By 90 days: Own a workflow from design through deployment, with evaluations, monitoring, and a measurable improvement in reliability or staff effort.
Within 6 to 9 months: Take responsibility for a core part of the product, make it easier to operate and extend, and help new engineers become productive as the team grows.
We will agree on priorities as we learn from deployments. Success means more workflows completed correctly, less manual intervention, and systems the team can confidently operate and extend.
Competitive base salary, with potential equity participation. Compensation, benefits, and any equity component will be discussed during the hiring process, based on your experience and the scope of the role.