Senior/Staff Full-Stack Engineer

Tahoe Therapeutics is a biotechnology company pioneering a fundamentally new approach to drug discovery, one that begins with the biology of real patients. Our Mosaic platform is the first to make in vivo data generation scalable, with single-cell resolution, allowing us to map how drugs affect patient-derived cells in the body across a wide range of biological contexts. We are building the world’s largest in vivo single-cell perturbation atlas and using it to train multimodal foundation models that learn the context-dependent nature of gene function, disease progression, and drug response.

By combining cutting-edge Machine Learning with the most biologically relevant datasets ever assembled in drug discovery, our mission is to find better drugs, faster and bring them to more patients who need them.

Tahoe is building AI-native tools that change how drug discovery gets done. Our flagship agentic product, Tara, is becoming the connective tissue across our platform: the way scientists, engineers, and models interact with our data, our models, and each other. Tara has to feel effortless while doing hard things underneath, including real-time reasoning, secure integrations, streaming interfaces, and multi-agent orchestration.

As a Senior/Staff Full-Stack Engineer, you will own product surface end-to-end and partner with our engineers, computational scientists, and ML team to make Tara robust, delightful, and secure. This role is well-suited for someone who has shipped real products at small teams, cares about the last mile (reliability, security, taste), and gets energy from working on AI-native problems where the right pattern is still being invented. We are looking for non-incremental thinkers who bring strong judgment on when to move fast, when to slow down, and when to reach for the right tool rather than build from scratch.

• Deep experience as a full-stack or product engineer at a startup or fast-moving team.

• Track record of owning ambitious products end-to-end (frontend, backend, database, deployment) from concept to production.

• Comfortable across a modern web stack and thoughtful about when to reach for which tool.

• Proven track record of building reliable and secure applications at scale.

• Strong communication and collaboration skills in a small team where boundaries between roles are fluid.

• Experience integrating LLMs or agents into production systems: streaming responses, tool orchestration, multi-agent coordination, or long-running autonomous workflows.

• Experience with observability and tracing for LLM or agentic systems (structured traces, cost attribution, replay, debugging when something goes wrong three tool calls deep).

• The mindset of an early engineer at an AI-native or fast-moving startup: high ownership, comfort with ambiguity, and bias toward action balanced with judgment.

• Interest in drug discovery, biology, or scientific tools. No formal background required, passion and curiosity are enough.

• Build Tara's end-to-end product surface: frontend, backend, real-time infrastructure, secure integrations.

• Partner with engineers and scientists to translate research capabilities into product experiences our users love.

• Tara is just the start. Build the next wave of AI-native tools and integrations that accelerate drug discovery at Tahoe.

• Set the bar for full-stack craft on the team: how we approach reliability, real-time UX, product velocity, and debugging.

• Unlimited Paid Time Off (PTO).

• Monthly Lunch budget

• One-time Office set up budget

• US Employees: HMO Kaiser Platinum and PPO Anthem Gold medical as well as vision and dental plans for both the employee and dependents.

The expected base salary range for this position is $150,000–$250,000. Actual compensation will depend on experience, skills, and location.

This position requires on-site presence at our South San Francisco office a minimum of three days per week.

We welcome applications from candidates in both Toronto, ON or San Francisco, CA, regions or those willing to relocate to the Bay Area or the Greater Toronto Area. Please note, we have one role open to two geographical locations.