Manager, Engineering

What You'll Do

Delivery

● Lead sprint delivery for a team of 6–12 engineers: planning, dependencies, risks, release readiness.

● Think about how work gets sequenced across people and AI-assisted workflows, not just story points.

● Keep JIRA, ProductBoard, and the dependency tracker current. No stale tickets, no surprises at SoS.

● Track cycle time and escaped defects; own the trend, not just the number.

Technical

● Review code and AI-generated output for whether it solves the right problem. Clean tests aren't enough.

● Define what needs human sign-off, what can be spot-checked, and what warrants a second pass.

● Write specs that work as contracts: clear scope, explicit constraints, stated boundaries.

● Stay close to architecture decisions, tech debt, and incident response.

● Contribute to software architecture decisions and patent writing for innovative work.

People

● Run 1:1s that are about growth, not sprint status.

● Coach engineers on when to trust AI output and when to push back. Model it explicitly, not just in retrospect.

● Give clear, timely feedback; build real development plans; address performance early.

● Help your team see that directing AI well is a skill worth building, not just a tool to adopt.

● Calibrate hiring panels, provide written feedback, contribute to calibration discussions.

Cross-functional & Culture

● Be the PM partner who holds a definition-of-ready and surfaces risks before they land in a leadership meeting.

● Engage escalations directly; produce RCAs; own P1/P2 support SLAs.

● Set the tone on your team: accountability, directness, recognition of others' work.

● Watch for workload and wellbeing signals before they become problems.

● Lead by influence across teams and functions ; comfortable driving cross-team technical decisions without direct authority

What We're Looking For

Experience

● 10+ years in software engineering, including 2+ years managing teams of 5 or more.

● BS/MS in Computer Science, Software Engineering, or a related field.

● Enough architectural depth to evaluate tradeoffs, including in AI-assisted output.

● Background in platform, API, data, or infrastructure engineering.

● Comfortable in a PM/Design pod environment; fluent with JIRA and ProductBoard or equivalent.

● Strong fundamentals in data structures, design patterns, and object-oriented programming.

● Proficient in Python or Java; enough depth to engage meaningfully in code review and design conversations.

● Strong enough in distributed systems, data pipelines, or APIs

What Sets You Apart

● You've run a platform or infrastructure team where other engineers are your customers.

● You've coached an IC through a meaningful promotion and can say concretely what that looked like.

● You've worked with AI-assisted engineering workflows and have a practical approach to reviewing output, not just a philosophy about it.

● You've collaborated across time-zones and know how to make it work.

● You can adopt a framework before it's perfect.