Decagon’s Product Engineering team builds the platform customers use to create, operate, and improve AI agents. The work turns engineer-dependent tasks into self-serve capabilities that CX teams can run themselves, with guardrails and tooling that improve reliability across production. You’ll collaborate closely with product and design to deliver end-to-end features, from architecture and deployment to the iteration that follows real customer usage, at a scale used by companies including Hertz, American Airlines, and Notion across chat, voice, email, and SMS.
Location: New York, NY (onsite)
Compensation: USD 200,000 - 400,000 per yearly + Offers Equity
Experience: 7+ years
What you’ll build
In this role, you will design and build systems that let customers configure, train, test, and monitor AI agents with confidence. The focus is on strong engineering underneath and clear abstractions on top, so the platform supports diverse enterprise use cases without forking per customer. You’ll also run evaluations on new text and voice models and integrate those that win into production traffic.
Responsibilities
- Reduce manual effort by creating self-serve functionality for agent configuration, training, and deployment
- Design configuration abstractions that balance flexibility and simplicity for non-technical teams across enterprise scenarios
- Build AI-powered tooling enabling CX and ops teams to create and manage complex agent workflows without writing code
- Develop monitoring, tracing, and analytics that expose actionable signals, including where an agent is failing and why
- Work on agentic systems at scale, including critical flows used by Fortune 100 companies
- Conduct evaluations on new text and voice models, then integrate winning models into production traffic
Requirements
- 7+ years building software products with strong product thinking
- Proficiency in Python and comfort working across the entire stack
- Ability to translate complex technical capabilities into simple, usable interfaces
- Experience with complex systems, including asynchronous programming and scale-related failure modes
- Strong debugging skills across deep technology stacks, using whatever tools get to the answer
- Skill in turning customer requests into clear, well-scoped product and technical specifications
- Practical judgment on when to move quickly versus when to slow down and build correctly
Team and collaboration
- Product Engineering builds the platform capabilities customers use to create, operate, and improve AI agents
- Frameworks support every agent in production, each with its own workflows, data, and constraints
- Working principle: failures seen in production become guardrails, evaluations, and tooling that prevent recurrence
- Engineers own features end to end, from technical architecture through deployment and iteration after launch
- Day-to-day collaboration with product and design, including discovery participation, requirement definition, design reviews, and launch iteration
Benefits
- 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 wellness, lifestyle, and work-life balance
- Daily lunches and snacks in the office
- Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)
Even better
- 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
- Experience working with multi-modal or voice models
