Senior Software Engineer, Enterprise Product

Decagon Decagon · Vertical AI · San Francisco, CA · Engineering

Senior Software Engineer on the Enterprise Product team at Decagon, a conversational AI platform company. This role focuses on building self-serve tools and platforms for customers to create, configure, train, and optimize AI agents for customer experiences. The engineer will translate complex AI capabilities into intuitive interfaces for both technical and non-technical users, owning features end-to-end.

What you'd actually do

  1. Eliminate manual engineering work by building self-serve functionality for agent configuration, training, and deployment
  2. Create AI-powered tools that enable non-technical teams to create and manage sophisticated workflows without writing code
  3. Design configuration abstractions that balance power and simplicity - handling diverse use cases while remaining accessible to non-technical teams
  4. Build monitoring and analytics that surface actionable insights, helping customers identify where their agents can improve
  5. Own features end-to-end, from technical architecture through deployment and iteration

Skills

Required

  • Python
  • TypeScript
  • full-stack development
  • product thinking
  • translating complex technical capabilities into simple, usable interfaces
  • balancing technical excellence with pragmatic shipping

Nice to have

  • 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

What the JD emphasized

  • building robust, scalable systems
  • self-serve functionality
  • AI-powered tools
  • sophisticated workflows
  • configuration abstractions
  • monitoring and analytics
  • technical architecture
  • building full-stack software products
  • strong product thinking
  • entire stack
  • complex technical capabilities
  • pragmatic shipping
  • building security-sensitive product systems
  • building developer tools, APIs, platforms, or internal tools that became customer-facing
  • LLMs, prompt engineering, or AI agent systems
  • asynchronous programming
  • building scalable systems
  • observability, data visualization, or analytics products

Other signals

  • AI agents
  • customer experience
  • self-serve products
  • platform