Software Engineer, Cloud Infrastructure

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. ROLE OVERVIEW  As a software engineer on Benchling's Infrastructure team, you will design, build, and operate the platforms, services, and tooling that let every Benchling engineering team ship and run software reliably, securely, and cost-effectively. Our work spans the foundations of our AWS environment: compute (Kubernetes/EKS), networking, secrets and identity, observability, infrastructure-as-code, and the economics of running all of it at scale. We hire software engineers for this team because strong programming, systems design, and problem-solving skills are the most durable foundation for infrastructure impact. You will independently scope and own meaningful, multi-quarter pieces of our platform end to end, from an ambiguous starting point to a production rollout and operational handoff, building paved roads that make the secure, reliable, and efficient path the default for engineers across Benchling. RESPONSIBILITIES Own projects end-to-end, from initial design and tech plan, to prototype, to production rollout and operational handoff. Design, build, and maintain internal applications, APIs, automation, and tooling (CLIs, Slack apps, serverless services, and AI-powered assistants) that support Benchling's cloud platform and infrastructure workflows. Own parts of our AWS foundation, including Kubernetes (EKS), networking, secrets and PKI, and the security and observability capabilities around them, with clear SLOs, runbooks, and actionable telemetry. Advance our infrastructure-as-code practices at scale: operate and improve our Terraform Cloud release system, reusable Terraform modules, and the tooling around them, with policy-as-code guardrails that let service teams self-serve safely. Drive cloud cost governance as an engineering discipline: build cost visibility and anomaly alerting, allocate shared platform costs to the services that drive them, analyze usage trends. Contribute to observability tooling, vendor relationships, and the cost and performance tradeoffs of our monitoring stack. Make architectural decisions that other teams build on, drive alignment across multiple teams, and help set technical direction and standards for the areas you own. Operate and improve production systems, including on-call, incident response, blameless postmortems, and root-cause analysis, and use what you learn to reduce toil. Partner with engineers across Benchling to understand internal customer needs, mentor teammates through design reviews and tech plan feedback, and help mature our tooling, best practices, and engineering processes. Check out our engineering blog for examples of past work. How We Run Terraform At Scale : how we operate Ter