About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.

About the Team

The Developer Platform team owns how Decagon builds and ships software: from the time an engineer/coding agent starts with an idea/spec/problem to the time the we have a released product in our customer’s hands. That covers dev environments, CI, the merge queue, build and test infrastructure, release and deploy, and the tooling and context that make coding agents useful in our codebase.

We're part of Infrastructure. Our users are the entire engineering team who ship to one shared monorepo every day, and a fast-growing number of coding agents working alongside them. Agents already open PRs, fix CI, and verify changes in cloud environments, using the same pipelines as everyone else. We measure success by how fast and how safely changes reach customers, whoever wrote them.

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.