Senior Engineering Manager

Gravie

11d•$194,000 - $258,500

About The Position

Gravie is seeking a technically engaged Senior Engineering Manager to lead its Carrier Integration and Platform Maturity teams, each staffed with a mix of full-time and contract engineers. Carrier Integration builds and operates integrations with insurance carriers, enrollment platforms, and HRIS/payroll providers, where data correctness directly affects members’ coverage and deductions. In partnership with Product Management counterparts, the manager owns outcomes for both teams, including what they ship and how reliably it runs in production. The role represents the teams in cross-team, leadership, partner, and vendor forums and brings decisions, priorities, and risks back to the teams. This role is central to Gravie’s adoption of agentic AI. Engineers use AI agents to develop specifications and plans and execute multi-step engineering work while retaining responsibility for guardrails, acceptance criteria, and shipped quality. The manager champions and measures effective adoption across both teams and helps build supporting tooling, workflows, and shared practices. The manager also uses AI in leadership work, applying appropriate judgment and review. The position actively improves team practices and delivery, and calls for direct involvement when needed—for example, reviewing merge requests, helping debug production issues, and critically reviewing architecture and designs. It also includes people development, vendor management, hiring, engineering quality, delivery oversight, cross-functional partnership, security coordination, and participation in the on-call rotation for critical production incidents.

Requirements

Prior experience managing multiple engineering teams simultaneously.
Experience leading teams that combine full-time and contract engineers.
A track record of developing people, including at least one example of growing someone into a lead or manager.
Experience building and operating integrations with third-party vendors and partner APIs.
Experience building systems that handle PHI/PII in a regulated environment, such as HIPAA or similar.
Strong written and verbal communication with senior cross-functional stakeholders.
Strong command of Scrum and Kanban and the judgment to know when each fits.
Experience maintaining risk and dependency tracking, such as RAID logs.
Comfort with on-call responsibilities and managing critical production incidents.
Practical experience with AI coding agents and agentic development workflows, and a track record of driving team AI adoption, including building tooling or practices adopted by others.
Concrete examples of using AI to lead more effectively, beyond driving team adoption.
Technical depth to review merge requests, help debug production issues, critically review architecture and designs, and spot gaps in a test suite; day-to-day production coding is not required.
Creative problem-solving ability and judgment about when to investigate directly and when to escalate.
Curiosity about how AI is changing the way engineering teams plan and deliver.

Responsibilities

Set clear expectations for all team members, including full-time and contract engineers, and manage performance against them, including difficult conversations.
Represent the teams in cross-team and leadership forums, partner and vendor calls, RAID log reviews, and Go/No-Go meetings; communicate decisions, priorities, and risks.
Identify blockers early, coordinate with owners across teams and vendors to resolve them, and escalate when needed.
Maintain visible delivery health through accurate Jira status and sprint commitments, timely stakeholder updates, and early risk communication.
Assign a named owner and due date to every epic, incident action item, and production-readiness checklist, and drive each to closure.
Own engineering quality across both teams, including test strategy, service contract tests, CI quality gates, and production-readiness reviews before go-live.
Ensure team ceremonies are effective, including standups, backlog refinement, sprint planning, sprint reviews, and retrospectives, personally or in partnership with Product and engineering leads.
Evolve team practices as AI changes software delivery by researching emerging practices, running experiments, and bringing the teams along.
Lead a blended team of full-time and contract engineers, managing capacity and alignment with Gravie priorities.
Coach and mentor direct reports through regular one-on-ones, individual development plans, and timely, candid feedback.
Develop engineers into leads and future engineering managers.
Manage vendor partners end to end, including statements of work, staffing plans, change orders, performance, and knowledge transfer.
Hire and develop full-time engineers as key capabilities move from contract to in-house teams.
Partner with Product, Data, Security, and Infrastructure to translate ambiguous business problems into clear, deliverable work.
Partner with Security to ensure appropriate handling of PHI/PII and ownership and resolution of security findings.
Lead effective adoption of agentic AI practices across both teams, set expectations for agent use, measure outcomes, and help engineers improve problem framing, guardrails, acceptance criteria, and risk identification.
Build and contribute to tooling, workflows, and shared practices that help teams get better results from AI agents.
Use AI in leadership work such as planning, identifying delivery risk, drafting decision documents, preparing for one-on-ones, and reporting, with appropriate judgment and review.
Participate in the on-call rotation for critical production incidents and drive follow-up and post-incident improvements.
Review merge requests, help debug production issues, review architecture and designs, and identify gaps in test suites as needed.