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Engineering Manager, Insights

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Decagon
Full Time position
Listed on 2026-01-20
Job specializations:
  • IT/Tech
    Technical Support, Data Science Manager, AI Engineer, Data Analyst
Job Description & How to Apply Below

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.

Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience ’ve raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.

About the Team

The Insights team builds the product surfaces that help customers understand what is happening in their agent conversations and improve agent quality over time. We turn large volumes of unstructured conversation data into clear explanations, intuitive workflows, and actionable next steps.

Our work spans three core areas:

  • Visibility and reporting: help teams track performance, trends, and drivers of customer outcomes across channels.

  • Proactive quality and risk detection: continuously surface issues like emerging failure modes, regressions, or policy and compliance risks, so teams can respond before they impact customers.

  • Actionable recommendations: guide users toward concrete improvements, including suggested updates to agent instructions, knowledge, and workflows based on real conversation patterns.

We own and scale a set of analytics and quality products today, and we are building new ones that deepen how customers learn from their data, diagnose issues, and iterate on agent behavior.

About the Role

This is a product focused, technical leadership role responsible for scaling existing analytics experiences and building new 0 to 1 products that help customers learn from their data and take action quickly.

You will partner closely with Product, Design, Customer Success, Data Science, and Agent Engineering to identify customer needs, propose new product directions, and ship iteratively based on real usage. Success requires strong people leadership, crisp execution in ambiguous spaces, and the technical judgment to set architectural direction across full-stack product surfaces and the data systems behind them.

In this role, you will
  • Build, lead, and develop a high performing team, including hiring, coaching, and performance management.

  • Own the engineering strategy, roadmap, and execution, balancing iteration speed with correctness, trust, and scalability.

  • Partner closely with Product and Customer Success to understand customer needs, propose new product directions, and ship iteratively based on real usage.

  • Drive 0 to 1 development through rapid prototyping, experimentation, and iterative deployment, then scale what works.

  • Set architectural direction across user facing experiences and the underlying data models, pipelines, and APIs that power reporting, detection, and insight generation.

  • Establish standards for data quality, metric integrity, observability, and debuggability so we can diagnose issues quickly and prevent repeat incidents.

  • Collaborate with Data Science, Research, and Agent Engineering to connect conversation signals, evaluations, and customer outcomes into actionable product experiences.

What success looks like
  • Customers can quickly understand what is happening in production and take action with confidence.

  • The team consistently ships new analytics workflows from 0 to 1, then improves adoption and impact through iteration and refinement.

  • Data quality, metric integrity, and observability are strong enough that we can debug issues quickly and prevent repeat incidents.

  • Cross functional execution is smooth across Product, Customer Success, Agent Engineering, Data Science, and Research.

  • The team grows into a high performing group with strong ownership, craft, and velocity.

You might thrive in this role if you
  • H…

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