Software Engineer, Tools and Automation

We are rebuilding biotech for the AI era.

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. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma.

We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today.

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. The world's most innovative biotech companies use Benchling's R&D Cloud to power the development of breakthrough products and accelerate time to milestone and market. Come help us bring modern software to modern science.

Benchling is building AI & Data Engineering, a small autonomous team within our Security & IT organization. We own two things: the internal AI capabilities and adoption so Benchlings can rapidly experiment and discover what works; and the source-of-truth data & analytics infrastructure the company depends on. We span the bridge between departmental AI experimentation and enterprise-grade agentic systems in production — rapidly prototyping new solutions, and graduating proven prototypes into hardened, well-governed systems with full SDLC rigor. This is an internal tools and automation role - think of it as an internal forward-deployed engineer. You will sit with the teams whose work you are automating, scope the problem with them directly, and ship the system that fixes it. AI is what we are supporting, but not directly what we build: we want someone who builds reliable internal systems and integrations, and who reaches for a model when a model is genuinely the right answer. Model research or ML engineering experience is neither required nor the bar.

We're built to be enablers. We set the patterns, standards, and shared infrastructure that let departmental teams and AI power users across the company build their own solutions, and we take on the agentic systems that no single team owns. It's early days for enterprise agentic AI at Benchling, and we'll be moving fast — iterating on prototypes, learning from internal customers, and changing direction as the field matures.

As the founding engineer for this team, you'll own the technical direction, architecture, and delivery of our internal tooling and automation portfolio. You'll be a player-coach — hands-on most of the time, leading by doing — and partner closely with our AI Product Manager on prioritization and our Data Analytics & Science team peers on the data foundations that agentic systems depend on. This is an individual contributor role on a flat team: you'll lead the engineering team in ideation, planning, and delivery and you'll drive technical hiring, while people management responsibilities sit with the hiring manager.

Check out our engineering blog for examples of past work across Benchling.

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• 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.

• Experience building internal developer platforms or internal tools at scale.

• Direct experience coaching or enabling non-engineers (analysts, ops staff, business power users) to build with AI tooling.

• Model research or ML engineering.

We offer a flexible hybrid work arrangement that prioritizes in-office collaboration. Employees are expected to be on-site 3 days per week (Monday, Tuesday, and Thursday).

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We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.

We are an equal opportunity employer. That means we don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. 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.