Senior Engineering Manager

What You'll Do
You're accountable for the organization you lead — delivery, technical judgment, production health, and how your teams work with AI — operating across multiple teams rather than inside a single one:

Build and grow a strong engineering organization, not just a single team. Create clarity, accountability, and growth so multiple teams — and the managers or leads within them — can take on increasing scope and perform at a high bar.
Create a credible delivery system across teams. Make priorities, ownership, dependencies, and capacity visible across the group you lead, and resolve the tradeoffs that no single team can make on its own.
Partner with Product and Design leadership on outcomes and execution at the domain level. Get pulled into discovery early, turn business priorities into executable plans across teams, and negotiate scope directly when AI-driven planning speed outpaces what engineering can safely validate and ship.
Hold the engineering bar across your organization. Ensure important technical decisions get the right depth of review everywhere you're accountable, and build the standards that make good judgment repeatable without your direct involvement in every decision.
Own the health of what your organization puts into production. Make sure every team you're accountable for can operate what it ships and respond effectively when things fail, and use delivery, quality, and reliability signals to know where to intervene and fix structural causes rather than recurring symptoms.
Set how your organization works with AI, and shape talent and standards around it. Define the delegation, verification, and review practices multiple teams adopt, evolve hiring and leveling criteria to reflect AI-native skills, and mentor other managers on coaching their engineers through the same shift.

What We're Looking For
You've led engineers and managers through the hard parts of scaling an organization. You've set expectations, coached people at different levels, managed performance, supported career growth and promotions, and handled difficult conversations directly — across more than one team.
You have technical depth engineers and managers trust, across more than one technical domain. You can engage meaningfully in design reviews for Java, Python, C#, or similar systems, challenge API contracts and data models, and reason about failure modes and testing strategy well enough to hold other managers accountable for the same rigor.
You've owned production engineering across multiple teams running on AWS or Azure. You've been accountable for observability, SLOs, on-call, incident response, and postmortem follow-through at a scale beyond a single team's services.
You know how to lead an organization that builds secure, privacy-sensitive systems. You can challenge authentication and authorization decisions, ensure threat modeling and sensitive-data handling are addressed up front across teams, and drive security findings through remediation. Experience with PHI/HIPAA or comparable regulated environments is preferred.
You run engineering with evidence, not anecdotes, at the organizational level. You've used delivery, quality, reliability, and team-health signals — cycle time, deployment frequency, change failure rate, escaped defects, MTTR, or operational load — to compare teams fairly, decide where to intervene, and report meaningful progress to leadership.
You improve the system instead of becoming the system, at a scale beyond one team. You create teams and managers who can make decisions and move independently, remove organizational friction a single EM can't fix alone, and treat dependency on you as something to eliminate, not evidence of your value.
You've led AI-first engineering in practice, and shaped how other managers do the same. You've directed agents on real work, established how engineers delegate and verify meaningful implementation, and helped other managers adapt their teams' operating model as the bottleneck moved from implementation to specification, review, or decision-making.