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Salary: USD 200,000 - 400,000 / annual
Decagon is a conversational AI platform enabling enterprises to deploy AI agents for customer support and operations across voice, chat, email, SMS, and other channels. Customers include Avis Budget Group, Block's Cash App and Square, Chime, Oura Health, and Hunter Douglas. The company is backed by a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures.
The Product Engineering team builds the platform that customers use to create, operate, and improve their AI agents. The team transforms work that currently requires engineers into self-service product that CX teams can operate independently. Engineers own features end-to-end, from technical architecture through deployment and post-launch iteration.
In this role, you will design and build systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. You'll eliminate manual work by building self-serve functionality for agent configuration, training, and deployment. You'll design configuration abstractions that balance power and simplicity across diverse enterprise use cases while remaining usable by non-technical teams. You'll build AI-powered tooling that enables CX and ops teams to create and manage complex agent workflows without writing code.
You'll also build monitoring, tracing, and analytics that surface actionable signal so customers can see where an agent is failing and why. Your work will handle agentic systems at scale, touching critical flows for Fortune 100 companies. You'll run evaluations on new text and voice models, then integrate winning models into production traffic.
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 ensure what you're building is right for them.
REQUIREMENTS:
- 4+ years building software products with strong product thinking
- Proficient in Python, comfortable working across the entire stack
- Experience translating complex technical capabilities into simple, usable interfaces
- Complex systems instincts, including asynchronous programming and failure modes that appear at scale
- High degree of comfort debugging system failures in deep technology stacks using whatever tool gets you to the answer
- Knack for turning customer asks into clear, well-scoped product and technical specs
- Judgment about when to ship fast and when to slow down and build it correctly
PREFERRED:
- Background with LLMs, prompt engineering, evals, or AI agent systems
- Experience building developer tools, APIs, platforms, or internal tools that became customer-facing
- Experience with observability, data visualization, or analytics products
- Experience building security-sensitive product systems such as authentication and data access controls
- Work with multi-modal or voice models
About Decagon
AI / Data / Infrastructure; SaaS / Enterprise Software — AI agents for customer support and enterprise operations.
