Senior Engineering Manager at ComPsych Corporation

Job description

ComPsych Ⓡ is the worldwide leader in organizational mental health, well-being, and absence management, dedicated to igniting human potential in workplaces across the globe. For over 40 years, we have combined the best in technology with unmatched human expertise to help individuals and their organizations thrive. Our GuidanceResources Ⓡ and AbsenceResources Ⓡ solutions deliver end-to-end mental health, well-being, work-life, health navigation, and absence support to more than 75,000 customers worldwide, touching more than 160 million lives across 200 countries. Visit compsych.com to find out why 40% of the Fortune 500 choose ComPsych for their mental health and absence management needs. We're modernizing how ComPsych builds technology — new customer-facing web and mobile experiences, a unified design system, and AI-powered capabilities across our products. That means raising the engineering bar for how we design, build, and operate software, with Engineering, Product, and Design working together end to end. AI is part of how we engineer, not a productivity add-on. Our engineers use agentic development as standard equipment — writing clear specs, delegating meaningful work to AI agents, and applying strong technical judgment to what comes back. Our platform carries behavioral health data for millions of members, so reliability, privacy, and correctness are non-negotiable — not a tax on velocity. As a Senior Engineering Manager, your organization is your product: you're accountable for what multiple teams ship, how the group operates as AI changes the job, and the managers and engineers who grow under your leadership. Your job isn't to run any one team day to day — it's to create the conditions, standards, and talent pipeline that let several strong teams move with high ownership and autonomy. 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. • 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. Bonus: experience managing other engineering managers, leading an organization through a similar AI-native transition, or shaping hiring and leveling criteria at the org level. • Full benefits package, including Paid Time Off (PTO), medical, dental, vision, 401(k) with match, robust EAP, wellness program, and much more • The salary range for this position is $225,000 - $275,000 (USD). The base salary range represents the anticipated low end and high end of the range for this position. The actual compensation will be influenced by a wide range of factors including, but not limited to previous experience, education, pay market/geography, and scheduled hours. EEO ComPsych is an equal opportunity employer. All applicants will be considered for employment regardless of race, color, age, genetics, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status and any other characteristic protected by federal, state or local laws. ComPsych Corporation maintains a drug free workplace. ComPsych Corporation and its affiliates is committed to the responsible and transparent handling of your personal data. Information collected during the recruitment process will be used to assess your application and, where applicable, to prepare and administer an offer of employment. Your personal data will be processed in accordance with the privacy laws applicable in your country or jurisdiction of residence, which may include the California Consumer Privacy Act (CCPA), the EU General Data Protection Regulation (GDPR), Canada's Personal Information Protection and Electronic Documents Act (PIPEDA) and applicable provincial privacy legislation, and other applicable national or local privacy laws. For full details on what personal data we collect, how we use it, your rights as an Applicant, and how to contact us with privacy-related questions, please review the relevant Applicant Data Privacy Notices: US Applicant Data Privacy Notice & Canada Data Privacy Notice .

Requirements

Must-haves

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:
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.

Nice-to-haves

Bonus: experience managing other engineering managers, leading an organization through a similar AI-native transition, or shaping hiring and leveling criteria at the org level.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

design systemaijavapythonapiawsazure

Platform: icims
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off

Wellness