Benchling
Software Engineer, Tools and Automation
San Francisco, CA · Senior
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About the role
- Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day.
- But moving at the new speed of science requires better technology.
- Benchling's mission is to unlock the power of biotechnology.
Responsibilities
- Where a workflow genuinely calls for an agent, own that architecture too: tool integration, state management, and evaluation.
- Make clear build vs. buy decisions across the stack with documented rationale.
- Build and ship the early portfolio yourself: Write production code at least half your time, particularly during the team's first year.
- Stand up the CI/CD, testing, and deployment infrastructure the team runs on - leveraging existing patterns from Benchling's Build organization wherever possible.
- Graduate departmental prototypes into hardened, production-grade systems and own production support under a "you build it, you run it" model.
- Design for enterprise from day one: Build for multi-tenant isolation, secrets management, audit logging, payload encryption, role-based access controls, and human-in-the-loop controls calibrated to risk.
- Partner with Security Engineering on threat modeling for the systems you build - including the agentic ones, where prompt injection, tool misuse, and data exfiltration are live concerns.
- Enable builders across the company: Coach power users and departmental teams on production patterns, develop the criteria that decide which prototypes graduate into enterprise-grade systems, and build the internal-facing developer experience - templates, SDKs, sandboxes - that lets builders outside this team ship safely.
- Partner across functions: Work closely with our data analytics peers on the source-of-truth datasets and pipelines that agentic systems depend on.
- Sit down with department leaders and non-technical stakeholders, turn a vague "this process is painful" into a scoped and prioritized engineering problem, and drive it to a shipped system - largely on your own judgment.
Requirements
- You have wired together APIs, SaaS platforms, and internal services, and you owned the result in production.
- Production experience with at least two of: Python, TypeScript/Node.js, Go
- comfort with working across the stack.
- Track record of going from zero to one: a platform, function, or product area you built up from scratch and scaled.
- Experience operating in regulated or security-sensitive environments.
- Model research or ML engineering experience is neither required nor the bar.
- 7+ years of professional software engineering experience building production systems, with strong systems design and integration fundamentals.
- A track record of building internal tools, automation, and systems integrations that colleagues depended on daily - not customer-facing product work alone. You have wired together APIs, SaaS platforms, and internal services, and you owned the result in production.
- Demonstrated understanding of how to optimize workloads across deterministic and non-deterministic capabilities, striking the right architectural balance for the needs of the specific solution being implemented.
- Practical experience applying LLMs where they earn their place in a workflow - and the judgment to recognize where they do not. We care that you shipped something that worked and that people kept using, not which framework you reached for.
- Experience operating in regulated or security-sensitive environments. Solid grasp of enterprise security fundamentals - encryption, access controls, audit logging, secrets management.
- Comfortable exercising technical leadership independent of positional authority. You set direction, raise the bar in design reviews, and grow other engineers through influence.
- Build software with a product-first approach. You ship code quickly and care about the real-world impact of your work.
- Enjoy ownership and building key pieces of platforms.
- Strong communication skills with non-technical audiences specifically. You can sit with a finance, legal, or sales ops team, understand their workflow well enough to challenge it, and come back with an engineering plan they recognize as their own problem - then explain the tradeoffs in their language.
- Interest in learning more about life science (prior knowledge is not required).
Nice to have
- Background in enterprise SaaS, life sciences, or biotech.
- Familiarity with LLM orchestration and tool-integration patterns (MCP, agent SDKs from major model providers).
- Experience with async orchestration (Temporal, Prefect, Airflow) applied to long-running or agentic workflows.
- Familiarity with SOC 2, HIPAA, or GxP compliance as they apply to AI systems.
- Model research or ML engineering.
- Benchling welcomes everyone.
- We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.
- We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.
Skills
- When a breakthrough is delayed, the world waits.
- Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps.
- AI has the potential to change this, compressing decades of R&D work into years.
- But that only happens when clean, structured scientific data and AI are built into how science gets done.
- Benchling is the AI platform for biotech R&D.
Company info
- Coach power users and departmental teams on production patterns, develop the criteria that decide which prototypes graduate into enterprise-grade systems, and build the internal-facing developer experience - templates, SDKs, sandboxes - that lets builders outside this team ship safely.
- Partner across functions: Work closely with our data analytics peers on the source-of-truth datasets and pipelines that agentic systems depend on. Sit down with department leaders and non-technical stakeholders, turn a vague "this process is painful" into a scoped and prioritized engineering problem, and drive it to a shipped system - largely on your own judgment. Work with Benchling's platform and infrastructure teams to leverage existing capabilities rather than build parallel systems.
- Elevate engineering standards: Set the bar for code quality, testing and evaluation, documentation, and on-call practices. Drive technical hiring through interview loop design, bar-raising in interviews, and representing the team to senior candidates. Mentor engineers on the team and other AI builders across the company.
- Production experience with at least two of: Python, TypeScript/Node.js, Go; comfort with working across the stack.
This listing is sourced directly from Benchling's careers page and normalized into a canonical job model.