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Benchling is an AI platform for biotech R&D used by over 200,000 scientists globally, including major pharma companies like Sanofi and Moderna. The company is rebuilding biotech for the AI era by combining clean, structured scientific data with AI capabilities directly into research workflows.
As a Software Engineer on the Infrastructure team, you will design, build, and operate the cloud platforms, services, and tooling that enable Benchling's engineering teams to ship and run software reliably, securely, and cost-effectively. This is a high-impact role where you'll own meaningful, multi-quarter projects end-to-end—from ambiguous starting points through production rollout and operational handoff.
Key responsibilities include:
- Owning infrastructure projects end-to-end: design, prototyping, production rollout, and operational handoff
- Designing and building internal applications, APIs, automation, and tooling (CLIs, Slack apps, serverless services, AI-powered assistants) that support cloud platform and infrastructure workflows
- Owning critical AWS foundation components including Kubernetes (EKS), networking, secrets and PKI, with clear SLOs, runbooks, and actionable telemetry
- Advancing infrastructure-as-code practices at scale: operating Terraform Cloud, reusable modules, and policy-as-code guardrails for safe self-service
- Driving cloud cost governance: building cost visibility, anomaly alerting, cost allocation, and analyzing usage trends
- Contributing to observability tooling, vendor relationships, and monitoring stack optimization
- Making architectural decisions that other teams build on, driving cross-team alignment, and setting technical direction
- Operating production systems including on-call rotation, incident response, blameless postmortems, and root-cause analysis
- Partnering with engineers across Benchling to understand needs, mentor through design reviews, and mature tooling and processes
Benchling values AI fluency and expects all engineers to integrate AI tools into their day-to-day work. The company has published detailed engineering blog posts on running Terraform at scale and building LLM-powered Slack bots.
REQUIREMENTS:
- 8+ years of experience in software engineering, site reliability, platform, or infrastructure engineering
- Strong software engineering fundamentals (coding, testing, debugging, API and system design) with proficiency in at least one general-purpose language (Python, Go, or TypeScript)
- Hands-on experience with AWS (EC2, EKS, RDS, VPC, IAM, S3) and understanding of how compute, storage, networking, and security fit together
- Production experience with infrastructure-as-code, ideally Terraform at meaningful scale
- Working knowledge of Kubernetes and container-based platforms
- Track record of independently scoping and delivering complex, ambiguous, multi-month projects from proposal to production, including writing technical design documents and communicating tradeoffs
- Experience making architectural decisions that other engineers and teams build on, and driving cross-team alignment
- Comfort working across development and operations, diagnosing hard production problems under pressure, and participating in on-call rotation
- Clear written communication, good documentation practices, and collaborative approach with internal platform users
NICE TO HAVE:
- Cloud cost management experience (cost allocation, tagging strategies, commitment purchasing, unit economics)
- Secrets and PKI infrastructure experience (e.g., HashiCorp Vault)
- AWS networking at scale (VPC design, Transit Gateway, multi-region connectivity)
- Internal developer tooling experience (CLIs, bots, serverless services, LLM-powered tools like RAG on Amazon Bedrock)
- Observability platforms and vendor relationship management
- Infrastructure experience in regulated (GxP) or multi-region environments
- GitOps and policy-as-code experience
- Technical lead or mentor experience
- AI-assisted development tools experience
