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Engineering Manager, Assist — Superhuman Go

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: The Rundown AI, Inc.
Full Time position
Listed on 2026-02-21
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Superhuman offers a dynamic hybrid working model for this role, based in San Francisco. This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that helps foster trust, innovation, and a strong team culture.

About Superhuman

Grammarly is now part of Superhuman, the AI productivity platform on a mission to unlock the superhuman potential in everyone. The Superhuman suite of apps and agents brings AI wherever people work, integrating with over 1 million applications and websites. The company’s products include Grammarly’s writing assistance, Coda’s collaborative work spaces, Mail’s inbox management, and Go, the proactive AI assistant that understands context and delivers help automatically.

Founded in 2009, Superhuman empowers over 40 million people, 50,000 organizations, and 3,000 educational institutions worldwide to eliminate busywork and focus on what matters. Learn more at  and about our values here.

The Opportunity

We’re looking for an Engineering Manager to lead the Assist team within Superhuman Go. This is an opportunity to build and scale a pervasive AI assistant that constantly observes what people are doing and proactively surfaces agents that can help them in the moment — before they even have to ask.

Superhuman Go is our proactive AI assistant that knows what you know and offers help without you having to ask. We’re combining Grammarly’s decade-long investment in understanding user context across every application with Coda’s packs ecosystem connecting to over 800 tools. Grammarly has built an AI superhighway that works everywhere users do — and the Assist team is responsible for bringing thousands of agents to that highway, training models to match what users are doing with the agent that can help them most.

The Assist team sits at the heart of this vision. You’ll lead a team of 8+ engineers building the intelligence layer that understands what users are doing — across browser tabs, native applications, Superhuman Mail, and Coda Docs — and matches them with the right agent at the right time. This means training and evaluating models that interpret diverse user contexts, building the proactive surfacing system that decides when and how to offer help, and shipping polished user-facing experiences across multiple surfaces.

As an Engineering Manager on the Assist team, you will:

  • Lead and grow a team of 8+ engineers, providing mentorship, career development, and fostering a high-performance engineering culture.
  • Own the technical direction for proactive agent surfacing — from understanding user context to matching them with the right agent at the right time.
  • Drive the development of models that interpret user activity across applications and match it with relevant agents from our growing ecosystem.
  • Build evaluation frameworks to measure model quality and user impact, iterating rapidly based on what works.
  • Ship compelling user-facing products across our Chrome extension, native desktop application, and integrations with Superhuman Mail and Coda Docs.
  • Collaborate cross-functionally with product, design, ML research, and platform teams to deliver an end-to-end experience.
  • Move us from a world where users must come and ask for help to one where we proactively use our deep understanding of user activity to surface the agent that can help them most.
  • Balance technical ambition with pragmatic execution — shipping incremental value while building toward the proactive assistant vision.
Qualifications
  • Has 3+ years of engineering management experience leading teams of 5+ engineers, with a track record of hiring, developing, and retaining strong talent.
  • Brings hands-on experience training, fine-tuning, and evaluating ML models, with a strong intuition for model quality and data-driven iteration.
  • Has shipped user-facing products at scale, with a deep appreciation for UX quality and a bias toward getting value in front of users quickly.
  • Demonstrates strong technical breadth across browser/extension development, ML/AI infrastructure, and full-stack product engineering.
  • Has experience building systems that operate across diverse surfaces (browser…
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