Manager, Engineering

What You'll Do

• 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 Were 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 its perfect.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.