Engineering Manager

Job Description

Responsibilities

• Guide career development, manage conflicts, and nurture a positive work environment. 
• Develop career plans with team members, provide guidance on skill development, and follow up on their evolution. 
• Engage in regular 1:1s, give constant feedback, and create a safe environment for open discussion — including the discussions that follow an experiment that didn’t work. 
• Set clear goals, mentor the team, and foster a collaborative environment across a geographically distributed organization. 
• Encourage a culture of learning and improvement, provide technical guidance, and support team members in both technical and soft skills. 
• Conduct technical and hiring-manager interviews, train the team on interviewing techniques, and help us keep raising the bar as we grow. 
• Identify and address gaps in team capabilities and processes to enhance team efficiency and success.

Run a portfolio of experiments, not a delivery queue

• Partner with your tech leads, who own and drive the technical roadmap for their areas. Your job is not to be the sole source of ideas — it is to pressure-test them, sharpen them, make sure the strongest ones get resourced, and make sure the people generating them have the room and the support to do it. When you do bring an idea, you bring it as a peer in the technical conversation. 
• Make the calls the roadmap can’t make for you: which hypotheses get compute and headcount, which get another iteration, and which get a clear, documented “no.” A well-run negative result is a real outcome, and we treat it as one — but only if it’s declared, written down, and learned from. 
• Manage the trade-off between a committed improvement target you must hit this year and research bets that may not pay off for several quarters. You will re-cut that budget as evidence arrives, and you’ll be able to explain the reasoning to both your team and your stakeholders. 
• Bring rigor to how the team decides something worked. Offline results have to predict online behavior; a strong point estimate on a single evaluation window is a starting point, not a conclusion. You will be the person asking whether the improvement survives a rolling evaluation, whether it’s already captured by a change we shipped last month, and what would have to be true for it to be wrong. 
• Own delivery on a cadence. Independent experimental workstreams have to converge into a release candidate, get evaluated end to end, and ship — including the hard call to leave a workstream out of a release when it isn’t carrying its weight.

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