Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.

We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.

We're building AI-native development practices into how this team works at a foundational level. That means infrastructure design needs to account for a new kind of collaborator: AI agents that generate, deploy, and operate software. The Staff Infrastructure Engineer on this team won't just keep systems running — they'll define what safe, observable, AI-assisted infrastructure operations look like in practice, and set the standard for how the broader engineering organization follows.

What you'll work on

• How do we design infrastructure that makes AI-generated deployments safe to ship and easy to roll back?

• How do we instrument billing systems so that failures — billing miscalculations, entitlement gaps, payment errors — are detected immediately and unambiguously?

• How do we build infrastructure that scales with usage-based billing workloads without manual intervention?

• How do we make the developer experience on this team faster and more reliable — local environments, CI/CD pipelines, deployment tooling?

Responsibilities

• Own and evolve the infrastructure supporting Billing Platform services: compute, storage, networking, CI/CD, and observability

• Design and maintain IaC (Terraform) for billing system infrastructure on AWS; set module patterns and standards for the team

• Build and own observability systems — metrics, logging, alerting — with a focus on billing accuracy and payment reliability

• Define deployment patterns and runbooks that work well in an AI-agent-assisted development workflow: clear rollback procedures, safe promotion gates, automated validation

• Partner with software engineers on service design — bringing infrastructure constraints and operational requirements into the conversation before code is written

• Identify systemic risks and drive improvements that span team or organizational boundaries

• Lead incident response for billing system issues; own the on-call rotation and postmortem process

• Mentor engineers across the team; your technical judgment should raise the floor for everyone

Qualifications

• 8+ years in platform, infrastructure, or SRE roles supporting production SaaS systems at scale

• Deep AWS expertise: ECS or EKS, RDS (Postgres preferred), networking, IAM, cost management — you've operated these systems under real load and real incidents

• Expert-level Terraform; you've designed reusable module patterns and set standards others follow

• Experience building and owning observability stacks (Datadog, Grafana, or similar) at an organizational level — not just using them

• Strong familiarity with CI/CD systems — Jenkins, GitHub Actions, or equivalent — including pipeline design and developer experience ownership

• Kubernetes at an operational and architectural level

• A track record of identifying systemic risks and driving improvements that span team or organizational boundaries

• Security-first mindset: threat modeling, blast radius analysis, least-privilege by default, audit trails as a design requirement

• Strong written English; at Staff level, written communication is how you scale your influence across teams

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

What sets you apart

You don't wait for problems to be handed to you — you find them, frame them, and drive the solution. You've operated at a scope where your decisions affected multiple teams or systems, and you know how to build consensus and move work forward without direct authority. You've thought seriously about what infrastructure needs to look like when AI agents are generating and shipping code — safe deployment patterns, strong observability, clean rollback — and you want to help define that standard here. Experience with billing, payments, or financial systems infrastructure is a meaningful plus.

What to Expect

First 30 Days

You will ship code in your first week. We run an agent-first development workflow — infrastructure changes start with a plan, specifications are written before generation, and every change is reviewed before it merges — and onboarding is no exception. You will get hands-on with the infrastructure supporting Billing Platform services early, shadow on-call, and build a clear picture of the system before you start making bigger changes. By the end of 30 days you will have shipped real work and know where the most important problems are.

First 90 Days

You will have taken ownership of one or more infrastructure components and delivered an improvement from design to production with measurable impact. You will be an active participant in deployment and reliability discussions, bringing infrastructure constraints and operational requirements into the conversation early — before code is written. You will be a full participant in the on-call rotation and have begun shaping the team's technical direction.

One Year Outlook

You will be the team's trusted authority on billing infrastructure. You will have driven meaningful improvements to observability, deployment safety, or platform reliability — and your work will be directly visible in the resilience and correctness of systems that handle real financial transactions for millions of Docker users. You will have helped define what AI-agent-assisted infrastructure operations look like done right, and that standard will be visible beyond this team.

Docker considers sponsorship on a case-by-case basis based on business needs.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 13, 2024.

Please see the independent bias audit report covering our use of Covey here.

Perks

• Freedom & flexibility; fit your work around your life

• Designated quarterly Whaleness Days plus end of year Whaleness break

• Home office setup; we want you comfortable while you work

• 16 weeks of paid Parental leave

• Technology stipend equivalent to $100 net/month

• PTO plan that encourages you to take time to do the things you enjoy

• Training stipend for conferences, courses and classes

• Equity; we are a growing start-up and want all employees to have a share in the success of the company

• Docker Swag

• Medical benefits, retirement and holidays vary by country

• Remote-first culture, with offices in Seattle and Paris

Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be.

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