Engineering Manager, Agent Orchestration

Decagon•San Francisco, CA

2d•$280,000 - $430,000•Onsite

About The Position

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. The Agent Orchestration team builds the core execution layer that powers every agent interaction. We own the systems responsible for coordinating model reasoning, evaluating agent behavior, and ensuring agents behave reliably in real customer environments. We focus on correctness, reliability, and speed. Our work shapes how Decagon agents plan, decide, and take actions across millions of interactions. We’re looking for an Engineering Manager to lead the Agent Orchestration team. This is a highly technical, player/coach leadership role at the core of Decagon’s product. You’ll lead the team responsible for the runtime and control plane that powers every agent interaction—coordinating model reasoning, tool use, and evaluation in production—and own the technical strategy and delivery for the orchestration engine behind every customer conversation. You’ll hire and develop a high-performing team while staying close to architecture, debugging, and reliability. You’ll partner closely with Research, Infrastructure, Product Engineering, and Agent SWE to translate frontier model improvements into predictable, safe, and scalable agent behavior in real customer environments. Success requires strong people leadership, clear execution in ambiguous problem spaces, and the technical depth to drive correctness and operational excellence.

Requirements

Have 2+ years of engineering management experience leading high performing teams in fast-moving environments.
Have strong technical depth and an IC foundation that enables you to guide architecture, debug complex failures, and make sound trade-offs.
Have experience building distributed systems, execution engines, real-time platforms, or other high scale systems where correctness and reliability matter.
Have a track record of delivering multi-quarter projects through ambiguity, creating clarity for your team and stakeholders.
Care deeply about engineering craft and operational excellence, including testing strategy, observability, and incident learning.
Communicate clearly and collaborate well across Product, Research, and Infrastructure teams.

Nice To Haves

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.

Responsibilities

Build, lead, and develop a high performing team of engineers, including hiring, coaching, and performance management.
Own the technical strategy and roadmap for Decagon’s orchestration engine, balancing speed of iteration with correctness and safety.
Drive architecture for systems that coordinate complex reasoning and action flows at scale.
Set reliability, testing, and observability standards across the orchestration stack, and build an operating cadence that prevents repeated incidents.
Create frameworks and guardrails that enable fast, safe iteration on agent behavior, evaluation, and rollout.
Partner with Product, Research, and Infrastructure teams to define requirements, navigate tradeoffs, and ship multi-quarter initiatives that move core company metrics.