Engineering Manager, Revenue

• We are looking for a bar raiser— someone who leads from the front, raises the quality of technical decisions, sharpens execution, and sets a higher standard for how the pod builds
• 4+ years of people management experience, including hiring and driving performance
• Recent hands-on engineering experience
• A track record of raising engineering standards across code quality, review rigor, testing discipline, and architecture
• Fluency with AI-augmented development workflows. You use tools like Claude Code, Codex, Cursor, or similar as part of your real day-to-day workflow
• High standards for code quality, product craft, and execution
• Clear, direct communication. You give feedback promptly, set a high bar, and follow through
• The ability to inherit a team, quickly form an accurate read, and raise the standard without creating unnecessary drag

Desirable

• You will join a high-growth team and work with experienced mentors to scale the core platform behind our AI-driven products. This is a chance to build industry-defining technology in a collaborative, mission-driven environment
• We’re looking for people who want to shape the future of human potential with AI
• At Revenue.io, we’re building AI-native software that helps go-to-market teams win, grow, and communicate more effectively. Our platform is shaped by more than half a billion conversations processed over the years, and we’re entering a new chapter in how product craft, engineering rigor, and AI-native execution come together to create customer value
• We’re looking for an Engineering Manager to lead the Revenue pod, the team responsible for core product surfaces including conversation intelligence, Moments real-time coaching, meeting capture, and supporting services
• This role reports directly to the Chief Engineering & AI Officer and plays a critical role to the EPD org at large
• This is a player-coach builder role with an expected mix of roughly 70% hands-on building and 30% management
• Ship production code across the stack. You do not need to be a specialist in every layer, but you should be comfortable contributing wherever the work demands it
• Set the bar for AI-native engineering across the pod. Effectively leverage AI tools and workflows deeply in your own work and establish a higher standard for speed, depth, quality, and leverage than the team has today
• Raise the technical bar through strong design instincts, substantive code review, and sound architectural judgment
• Make pragmatic technical decisions that reduce rework, improve maintainability, and keep the team moving with high quality
• Raise the pod’s execution standard across planning, work breakdown, prioritization, unblocking, and delivery
• Partner closely with product on roadmap planning, execution, tradeoffs, and sequencing, bringing clarity and engineering judgment rather than passive delivery management
• Coach and develop engineers through direct, timely, actionable feedback against a clear performance bar
• Build a high-clarity, high-accountability team environment where people know what excellence looks like, where they stand, and what needs to improve
• What success looks like:
• The team ships high-quality work more consistently and with greater rigor
• Engineering judgment improves across the pod e.g., better decisions, stronger reviews, less avoidable rework
• The team operates with more clarity, ownership, urgency, and follow-through
• AI becomes a real force multiplier in how the team builds, not a side tool or sporadic experiment
• The pod becomes more trusted by product, design, and engineering peers
• The overall standard of the team is visibly higher six months from now because you joined