Engineering Manager, Go - Assist & Chat

Grammarly, now part of Superhuman, is an AI productivity platform focused on unlocking the superhuman potential in everyone. They are seeking an Engineering Manager to lead the Assist & Chat teams, responsible for building and scaling a proactive AI assistant that assists users by understanding their context and delivering help automatically.

Responsibilities:

• 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

Requirements:

• 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 extensions, native apps, web applications) and understands the unique challenges of each
• Shows a track record of managing ambiguity — defining strategy, making tradeoffs, and shipping in fast-moving, early-stage product areas
• Communicates clearly and influences effectively across engineering, product, design, and leadership
• Is energized by the challenge of building proactive AI experiences that anticipate user needs rather than waiting for explicit requests