## About the role
Science Machine is building agentic AI software for automating bioanalysis workflows. Our platform helps scientists and bioanalysis teams turn complex analytical processes into reliable, repeatable, AI-assisted workflows across data ingestion, analysis, reporting, review, and compliance.
We are looking for a Senior Full Stack Engineer to take ownership of both product and infrastructure development. This is a broad, hands-on engineering role for someone who is comfortable moving between user-facing product work, backend API design, database modelling, cloud infrastructure, Kubernetes workloads, and deployment pipelines.
You will work close to the core product: building interfaces scientists use every day, designing the systems that run agentic workflows, and hardening the platform as it moves from pilots into production customer environments.
## What you'll do
– Build product features across React, Next.js, and TypeScript.
– Design, build, and maintain backend Python backend services and APIs.
– Own PostgreSQL database design, data modelling, schema migrations, and query performance.
– Build and maintain infrastructure using Terraform, Docker and Kubernetes, on GCP.
– Improve the reliability, scalability, and maintainability of production systems.
– Take part in on-call support to investigate and fix production issues when they arise.
– Listen to user feedback, identify product opportunities, design practical solutions, test them with users, and ship improvements quickly.
– Work with scientists, customers, and the wider team to turn real bioanalysis workflows into robust product capabilities.
– Help shape engineering practices in a small, fast-moving technical team.
– Make pragmatic technical decisions across the full stack, balancing product speed with long-term system quality.
## Essential experience
– Strong full stack engineering experience with modern React, Next.js, TypeScript, and backend REST APIs.
– Strong Python backend/API development experience.
– Strong PostgreSQL experience, including schema design, migrations, indexing, and data modelling.
– Experience managing cloud infrastructure with Terraform.
– Experience running production workloads on GCP and Kubernetes.
– Strong CI/CD and Git workflow experience.
– Experience owning systems end to end, from design and implementation through deployment, monitoring, and debugging.
– Experience supporting and maintaining production services, including complex system migrations with minimal downtime.
– Comfort working in ambiguous, fast-moving environments where product and technical requirements evolve quickly.
## Nice to have
– Experience with security, access control, RLS, authorisation, or compliance-conscious product development.
– Experience with observability, incident response, production debugging, tracing, or reliability engineering.
– Experience building agentic AI systems, and sandboxed execution environments for running untrusted code.
– Experience with scientific, bioinformatics, cheminformatics, mass spectrometry, LC-MS, ADME, or regulated laboratory workflows.
– Experience with Stripe billing, subscriptions, and team account management.
## Essential qualities
– High ownership: you notice what needs doing and carry it through.
– Product-minded: you care about whether scientists can actually use what you build.
– Systems-minded: you can reason across frontend, backend, database, infrastructure, and deployment boundaries.
– Pragmatic: you choose simple, robust solutions and avoid unnecessary abstraction.
– Reliable under ambiguity: you can make progress when requirements are incomplete.
– Security-conscious: you understand the importance of permissions, auditability, and data boundaries.
– Clear communicator: you can explain technical decisions to engineers, scientists, and founders.
– Curious about science: you do not need to be a bioanalysis expert, but you should want to learn the domain.
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