Senior Software Engineer
Decagon
Senior Software Engineer
Decagon
Builds AI agents for enterprise customer support
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.
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.
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.
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
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.
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.
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.
$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.
Decagon builds AI customer support agents for large businesses, handling customer questions and requests over voice, chat, email, and text messages. Its platform connects these conversations to company records and internal tools, so an agent can check an order, change a reservation, or complete a support task. Customer experience teams define how agents should respond and when to pass a case to a person, while testing tools check behavior before changes reach customers. Businesses pay usage fees for the software, with charges tied to conversations or completed resolutions rather than the number of human support staff. Decagon was founded in 2023 and is headquartered in San Francisco.
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