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. About the role 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 https://benchling.engineering/ for examples of past work. How We Run Terraform At Scale https://benchling.engineering/how-we-run-terraform-at-scale-da7bb75dc394: how we operate Terraform Cloud across hundreds of workspaces and the custom tooling we built around it. Building an LLM-Powered Slackbot https://benchling.engineering/building-an-llm-powered-slackbot-557a6241e993: how we built a knowledge base on Amazon Bedrock that answers developer questions in Slack. Requirements 8+ years of experience in software engineering, site reliability, platform, or infrastructure engineering Have strong software engineering fundamentals (coding, testing, debugging, API and system design) and proficiency in at least one general-purpose language such as Python, Go, or TypeScript Have hands-on experience with AWS (for example EC2, EKS, RDS, VPC, IAM, S3) and understand how compute, storage, networking, and security fit together Have production experience with infrastructure-as-code, ideally Terraform at meaningful scale Have working knowledge of Kubernetes and container-based platforms Have a track record of independently scoping and delivering complex, ambiguous, multi-month projects from proposal to production, including writing technical design documents and communicating tradeoffs to technical and non-technical stakeholders Have made architectural decisions that other engineers and teams build on, and driven alignment across multiple teams Are comfortable working across development and operations, including diagnosing hard production problems under pressure and participating in an on-call rotation Communicate clearly in writing, document your work well, and enjoy collaborating with internal platform users Nice to have Experience with cloud cost management (cost allocation, tagging strategies, commitment purchasing, unit economics) Experience with secrets and PKI infrastructure such as HashiCorp Vault Experience with AWS networking at scale (VPC design, Transit Gateway, multi-region connectivity) Experience building internal developer tooling such as CLIs, bots, or serverless services, including LLM-powered tools (for example retrieval-augmented generation on Amazon Bedrock) Experience with observability platforms and managing vendor relationships for engineering tooling Experience operating infrastructure in regulated (for example GxP) or multi-region environments Experience with GitOps and policy-as-code approaches to infrastructure change management Experience as a technical lead or mentor Experience using AI-assisted development tools to accelerate engineering and operational work How We Work 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). #LI-Hybrid #BI-Hybrid #LI-CG1 Benchling welcomes everyone. 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.
