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Decagon

Builds AI agents for enterprise customer support

Engineering Manager - Research

Engineering LeadershipUpdated on Nov 10
Full-time

About the Job

Requirements

  • At least 5 years of industry experience building machine-learning systems involving language models, speech, agents, or model infrastructure.
  • At least 1 year of people-management experience and a strong individual-contributor background.
  • Deep experience post-training, evaluating, deploying, or serving foundation models at scale.
  • Strong technical judgment and a track record of translating ambiguous research ideas into measurable product outcomes.
  • Experience hiring, coaching, and developing technical talent, with clear communication across research, engineering, product, and executive stakeholders.

Responsibilities

  • Build, manage, and develop a high-performing team of research engineers through hiring, coaching, performance management, and career development.
  • Own the technical direction and roadmap for the area, prioritizing high-leverage investments across models, evaluation, safety, speech, and agent systems.
  • Turn open-ended research directions into focused programs with clear hypotheses, milestones, decisions, and measures of production impact.
  • Stay close to the technical work through architecture and experiment reviews, debugging, and individual contribution.
  • Set a high bar for experimental rigor, reproducibility, evaluation quality, engineering execution, and safe model rollouts.
  • Partner across Infrastructure, Agent Platform, Product Engineering, Product, and customer-facing teams to move research into production.

Desired Qualifications

  • A record of influential research, open-source contributions, or production machine-learning systems with significant real-world impact.

About the Company

Decagon

Builds AI agents for enterprise customer support

Decagon builds AI customer support agents for large businesses, handling customer questions and requests over voice, chat, email, and text messages. Its platform connects these conversations to company records and internal tools, so an agent can check an order, change a reservation, or complete a support task. Customer experience teams define how agents should respond and when to pass a case to a person, while testing tools check behavior before changes reach customers. Businesses pay usage fees for the software, with charges tied to conversations or completed resolutions rather than the number of human support staff. Decagon was founded in 2023 and is headquartered in San Francisco.

Company size
501-1,000
Company stage
Series D
Total funding
$481M
Headquarters
San Francisco, CA
Founded
2023

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