ABOUT THE ROLE
We're hiring an experienced engineer to own and grow the foundations of our developer platform. The team works on both traditional developer experience and AI leverage. This role leans toward the foundations: fast and reliable CI, reproducible environments, safe deploys, and clear tooling.
Those foundations decide how much leverage we get from AI. An agent is only as effective as its feedback loop: how quickly it can get a working environment, run the right tests, trust the result, and ship safely. Every improvement you make for engineers also helps agents, and you'll design with both kinds of users in mind.
You'll find where development slows down (slow or flaky CI, merge-queue churn, hard-to-reproduce environments, manual release steps), fix the system behind it, and get the fix adopted across the company.
WHAT YOU'LL WORK ON
CI and the merge queue: make CI faster, cheaper, and more reliable. That means test selection, caching, runner autoscaling and capacity, flaky-test detection and quarantine, and merge-queue throughput. With more agent-written PRs, merge-queue throughput and CI signal quality become even more important.
Release and deploy: improve the path from merge to production. That includes promotion between environments, canary and rollback safety, deploy gates, and release tooling that removes manual steps without removing control.
Agentic development tooling: Support various agents (Devin/Claude Code/Codex), their setup, the surrounding infra (eg Runlayer), and review agents like Greptile.
Tools and context: Give agents secure, observable access to codebases, tests, documentation, internal systems, and the tools needed to complete real engineering work.
Infrastructure as Code: We use OpenTofu for most of our IaC and use Spacelift to deploy them
Internal builder platforms: Create reusable frameworks that let teams quickly build their own internal tools, dashboards, automations, and agents.
Developer productivity observability and evals: instrument the whole development lifecycle for both human and agent work, and use that to guide project selection and agent evals
WHAT YOU'LL DO
Design, build, and operate the systems that every Decagon engineer and coding agent uses to build, test, and ship code.
Lead ambitious platform projects from an ambiguous problem through technical design, implementation, rollout, and long-term evolution.
Partner closely with engineers across the company to understand bottlenecks, prototype solutions, and drive adoption.
Improve the speed and quality of software development through better agent tooling, testing, review, and automation.
Own the reliability, observability, security, performance, and cost of the systems you build.
YOU MIGHT BE A GREAT FIT IF YOU
Have 4+ years of experience building production software, particularly in backend, infrastructure, platform, or developer tooling.
Are a strong programmer in Python, TypeScript, or another systems-oriented language.
Have designed and operated APIs, services, or platforms that other engineers depend on.
Understand distributed systems, cloud infrastructure, containers, and production reliability.
Have taken technically complex projects from ambiguous problem statements to widely adopted production systems.
Care deeply about developer experience and know how to turn complicated infrastructure into simple, useful abstractions.
Move quickly while maintaining a high bar for correctness, security, and operational quality.
Communicate clearly and enjoy working directly with the engineers who use what you build.
EVEN BETTER IF YOU HAVE
Experience building coding agents, tool-use systems, agent harnesses, or sandboxed execution environments.
Experience with CI/CD systems, build infrastructure, monorepos, or large-scale test automation.
Built evaluation, testing, or review systems for AI-generated code.
Experience with Kubernetes, infrastructure as code, secrets management, or identity and access systems.
Built an internal developer platform or shared tooling that achieved meaningful adoption across an engineering organization.
Applied AI to materially improve engineering velocity, reliability, or software quality.
COMPENSATION
$200K – $400K + Offers Equity
This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.
In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.
Benefits
We proudly offer the following benefits for our full-time employees
Medical, Dental, and Vision benefits for you and your family
Life Insurance and Disability Benefits
Retirement Plan (e.g., 401K, pension)
Parental Leave
Fertility and family building benefits through Carrot
Monthly stipend to support your wellness, lifestyle, and work-life balance
Daily lunches and snacks in the office to keep you at your best
Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
Decagon offers a competitive benefits package that varies by country and complements local statutory benefits. Details for this location will be provided during the recruitment process.