Senior Software Engineer, Billing

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 Senior Software Engineer, Billing on this team will keep systems running, help define what safe, observable, AI-assisted infrastructure operations look like in practice, and model that standard for the rest of the team.

The Billing Platform Engineering team owns the systems that make Docker's commercial model real. You'll work on problems like:

• 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?

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

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

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

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

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

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  Identify systemic risks in the team's systems and drive improvements, including work that reaches into adjacent teams or services

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  Participate in incident response for billing system issues. This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed.

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  Mentor engineers on the team; your technical judgment should help raise the bar for how the team builds and operates

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

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

• Strong Terraform skills; you've built reusable module patterns and can improve the ones a team relies on

• Experience building and owning observability stacks (Datadog, Grafana, or similar) for production services — not just using them

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

• Kubernetes at an operational and architectural level

• A track record of identifying systemic risks and driving improvements within your team and adjacent systems

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

• Strong written English; clear written communication is how you scale your work across the team

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

Operational ownership is part of the job. You’ll join the rotation after onboarding and shadowing, and help improve on-call itself: better alerts, stronger runbooks, less toil, and blameless postmortems aimed at prevention.

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 the systems your team owns, and you know how to build alignment 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.

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.

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 will be contributing to the team's technical direction.

You will be one of the team's go-to engineers 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.

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