Staff Software Engineer ( Foundation Platform)

Staff Software Engineer ( Foundation Platform) WHO WE ARE Atlan is building the missing context layer for data and AI, helping enterprises close the AI value chasm. Today, 95% of AI pilots fail because AI systems don’t understand the context behind data: what it means, how it’s governed, and how it should be used. Atlan connects to every part of the modern data and AI stack to unify this context into a single, shared layer that both humans and AI agents can rely on. With Atlan, teams can discover, understand, and trust their data; build and collaborate on a shared body of knowledge; and activate that context across analytics, operations, and AI workflows.Trusted by global enterprises like Mastercard, Workday, General Motors, Unilever, Ralph Lauren, FOX, Nasdaq, and Medtronic, we’re backed by world-class investors including GIC, Insight Partners, Meritech, Peak XV, and Salesforce Ventures What You’ll Own As an engineer on the Foundation Platform team, you will be responsible for the production infrastructure that powers Atlan’s context layer for AI across AWS, Azure, and GCP, using AI-assisted development tools (such as Claude Code and Cursor) as a natural part of your daily workflow. You will: - Own and evolve our multi-tenant infrastructure on Kubernetes, including dedicated clusters per customer and the full tenant lifecycle (provisioning, scaling, migration, and offboarding). - Make our GitOps deployments faster and safer by improving the ArgoCD and Helm based pipeline that deploys 1,000+ applications across hundreds of tenants. - Replace manual infrastructure runbooks (for example, Kubernetes upgrades, Private Link setups, DR drills, cluster onboarding) with reliable automation using Infrastructure-as-Code and workflow engines. - Strengthen observability and efficiency by improving our logging, metrics, and alerting stack and using it to drive better reliability, visibility, and meaningful cloud cost reduction. - Lead customer-facing infrastructure work and incidents end to end, and turn what you learn into clear runbooks, dashboards, and Claude Skills that help both humans and AI agents operate the platform. What You Bring - 7+ years in platform engineering, infrastructure, SRE, or backend systems at a SaaS company, with high ownership, strong written/async communication, and enthusiasm for AI-native development tools. - Deep hands-on experience operating Kubernetes in production: managing clusters, upgrades, networking and RBAC, and multi-tenant concerns, not just deploying apps. - Strong GitOps and Helm experience (for example ArgoCD or similar) at meaningful scale, including dealing with sync failures, drift, chart complexity, and improving deployment safety and speed. - Production-quality infrastructure automation skills in Go or Python; familiarity with TypeScript is a plus. - Solid cloud and Infrastructure-as-Code foundation: deep experience with at least one major cloud (AWS, GCP, or Azure), and having designed, written, and reviewed substantial Terraform or Crossplane modules. - Comfort debugging end to end across GitOps pipelines, Kubernetes, and cloud provider layers when deployments or tenants are stuck. - Experience with multi-tenant SaaS infrastructure, observability stacks (logs, metrics, traces, dashboards), and practical cloud cost optimisation (for example autoscaling, instance strategy, or savings mechanisms), ideally with exposure to workflow engines such as Temporal or internal self-service / developer platform tooling. What Great Looks Like: The ideal candidate: - Has led at least one major, cross-cutting infrastructure initiative end to end, such as a deployment pipeline overhaul, Kubernetes upgrade framework, multi-tenant migration, DR architecture, or cost programme, and can explain the system-level impact across reliability, cost, and developer experience. - Can walk through a Kubernetes and GitOps platform they have built or significantly evolved, and how they improved dep ... (truncated, view full listing at source)