Decagon Senior Software Engineer on Decagon's Enterprise Product team designs and builds scalable systems enabling customers to create and optimize AI agents. Focuses on building self-serve functionality and AI-powered tools for non-technical users.
Responsibilities
As a Senior Software Engineer on the Enterprise Product team, you will take ownership of designing and building robust, scalable systems that allow customers to create and optimize their AI agents with confidence. This means working closely with customer facing teams to understand current workflows, then designing elegant abstractions and interfaces that scale those capabilities across our customer base. You’ll work day-to-day with the core product and design teams, joining discovery, defining requirements, reviewing designs, and iterating through launch.
Eliminate manual engineering work by building self-serve functionality for agent configuration, training, and deployment
Create AI-powered tools that enable non-technical teams to create and manage sophisticated workflows without writing code
Design configuration abstractions that balance power and simplicity - handling diverse use cases while remaining accessible to non-technical teams
Build monitoring and analytics that surface actionable insights, helping customers identify where their agents can improve
Own features end-to-end, from technical architecture through deployment and iteration
Qualification
Proficient in Python and/or TypeScriptExperience building developer toolsBackground with LLMsExperience with observability
Required
4+ years building full-stack software products with strong product thinking
Proficient in Python and/or TypeScript, comfortable working across the entire stack
Experience translating complex technical capabilities into simple, usable interfaces
Track record of balancing technical excellence with pragmatic shipping
Experience building security-sensitive product systems, such as authentication and data access controls.
Experience building developer tools, APIs, platforms, or internal tools that became customer-facing
Background with LLMs, prompt engineering, or AI agent systems
Familiarity with asynchronous programming and building scalable systems
Experience with observability, data visualization, or analytics products
