Senior Software Engineer on Product Engineering, building self-serve configuration, training, testing, and monitoring systems for AI agents used by enterprise customers. Work includes monitoring and tracing tooling, configuration abstractions, and running evaluations on text and voice models. Stack centers on Python across the full stack, with asynchronous programming and debugging in deep technology stacks.
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
Product Engineering at Decagon builds all aspects of the platform our customers use to create, operate, and improve their AI agents. We turn work that currently requires an engineer into product that a CX team can run themselves.
This team is core to how Decagon scales. The frameworks we build support every agent we have in production, each with its own workflows, data, and constraints. We build the agents too, and that’s what keeps the platform honest: a failure mode we debug in production becomes a guardrail, an eval, or a piece of tooling that catches it everywhere.
Our agents run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS.
About the Role
You’ll design and build the systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. That means strong engineering underneath, and abstractions on top that hold up across different use cases without forking per customer.
You’ll work day to day with product and design: joining discovery, defining requirements, reviewing designs, and iterating through launch. You’ll stay close enough to customers to understand their use cases in depth and to ensure what you’re building is actually right for them.
Engineers here own features end to end, from technical architecture through deployment and the iteration after it.
In this role, you will
Your background and skillset look something like this
Even better
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:
These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Compensation: $200K - $400K
