Staff Software Engineer, Enterprise Product

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

Staff Software Engineer for the Enterprise Product team at Decagon, a conversational AI platform company. The role involves leading a full-stack product engineering team to build and scale the platform that customers use to create, maintain, and optimize AI agents. This includes driving technical direction, leading complex initiatives, creating AI-powered tools for non-technical users, building monitoring and analytics, and mentoring engineers.

What you'd actually do

  1. Drive technical direction for the team, to build enterprise ready platform that scale with our customer base and features, by applying the right architectural principles and design patterns.
  2. Lead complex initiatives from ambiguous requirements to shipped products
  3. Create AI-powered tools that enable non-technical teams to create and manage sophisticated workflows without writing code
  4. Build monitoring and analytics that surface actionable insights, helping customers identify where their agents can improve
  5. Partner directly with customers and cross-functional teams to identify opportunities and validate product direction

Skills

Required

  • 6+ years building full-stack software products
  • demonstrated impact on technical direction
  • strong product thinking
  • Deep expertise in TypeScript and/or Python
  • strong architecture and system design skills
  • Proven ability to design abstractions and platforms that serve diverse use cases elegantly
  • Track record of leading technical initiatives and driving consensus across teams
  • Experience balancing technical excellence with rapid iteration and customer needs
  • Strong product intuition
  • history of translating user feedback into technical solutions
  • History of mentoring engineers and establishing technical standards

Nice to have

  • Experience building security-sensitive product systems, such as authentication and data access controls.
  • Experience building and scaling developer tools, APIs, platforms, or infrastructure products
  • Familiarity with LLMs, AI agent systems, prompt engineering, or building products on top of AI capabilities
  • Familiarity with asynchronous programming and building scalable systems
  • Experience with observability, data visualization, or analytics products
  • History of establishing technical standards, design patterns, or architectural principles adopted across teams

What the JD emphasized

  • enterprise ready platform that scale
  • AI agents
  • optimize AI agents
  • sophisticated workflows
  • technical direction
  • scale

Other signals

  • AI agents
  • conversational AI platform
  • customer experiences
  • self-serve products
  • optimize AI agents