Engineering Manager, Agent Orchestration

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

Engineering Manager to lead the Agent Orchestration team, responsible for the core execution layer of Decagon's conversational AI platform. This role involves building and leading a team, owning the technical strategy for the orchestration engine, driving architecture for complex reasoning and action flows, and ensuring reliability, testing, and observability. The focus is on coordinating model reasoning, tool use, and evaluation in production to enable predictable, safe, and scalable agent behavior.

What you'd actually do

  1. Build, lead, and develop a high performing team of engineers, including hiring, coaching, and performance management.
  2. Own the technical strategy and roadmap for Decagon’s orchestration engine, balancing speed of iteration with correctness and safety.
  3. Drive architecture for systems that coordinate complex reasoning and action flows at scale.
  4. Set reliability, testing, and observability standards across the orchestration stack, and build an operating cadence that prevents repeated incidents.
  5. Create frameworks and guardrails that enable fast, safe iteration on agent behavior, evaluation, and rollout.

Skills

Required

  • 2+ years of engineering management experience leading high performing teams
  • Strong technical depth and an IC foundation
  • Experience building distributed systems, execution engines, real-time platforms, or other high scale systems
  • Track record of delivering multi-quarter projects through ambiguity
  • Experience with engineering craft and operational excellence, including testing strategy, observability, and incident learning
  • Clear communication and collaboration skills

Nice to have

  • Experience with agent frameworks, runtimes, orchestration logic, or tool use systems
  • Experience with evaluation, experimentation, or model quality measurement systems
  • Experience building guardrails for safety-critical or highly reliable systems

What the JD emphasized

  • high performing team
  • technical strategy
  • orchestration engine
  • correctness and safety
  • complex reasoning and action flows at scale
  • reliability, testing, and observability
  • frameworks and guardrails
  • agent behavior, evaluation, and rollout
  • high scale systems where correctness and reliability matter
  • delivering multi-quarter projects through ambiguity
  • engineering craft and operational excellence

Other signals

  • AI agents
  • conversational AI platform
  • agent orchestration
  • coordinating model reasoning
  • tool use
  • evaluation