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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 (Cash App/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-serve product that CX teams can operate independently. This team is core to Decagon's scaling strategy, building frameworks that support every agent in production with its own workflows, data, and constraints. The team also builds agents themselves, which keeps the platform honest: production failure modes become guardrails, evals, and tooling that prevents issues across the platform.
In this role, you will design and build systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. You'll work day-to-day with product and design teams—joining discovery, defining requirements, reviewing designs, and iterating through launch. You'll stay close to customers to understand their use cases in depth and ensure what you're building is right for them. Engineers here own features end-to-end, from technical architecture through deployment and post-launch iteration.
Key responsibilities include: eliminating manual work by building self-serve functionality for agent configuration, training, and deployment; designing configuration abstractions that balance power and simplicity across diverse enterprise use cases while remaining usable by non-technical teams; building AI-powered tooling that lets CX and ops teams create and manage complex agent workflows without coding; building monitoring, tracing, and analytics that surface actionable signal so customers can see where agents are failing and why; handling agentic systems at scale for Fortune 100 companies; and running evaluations on new text and voice models, then integrating winners into production traffic.
REQUIREMENTS:
- 7+ 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 tools necessary
- Knack for turning customer asks into clear, well-scoped product and technical specs
- Judgment about when to ship fast versus when to slow down and build correctly
PLUS (nice to have):
- 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 (authentication, 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.
