Sr. Manager, Engineering – AI & Innovation

J.D. Power•Ontario - Remote, ON

5d•$140,000 - $170,000•Remote

About The Position

This role is responsible for leading the AI & Innovation function, including direct leadership of the Innovation Crew and Launch Lab pods. The Senior Manager owns the people, roadmap, and outcomes, providing direction and growth opportunities for the team. This position ensures AI & Innovation operates as a stable, standalone function, translating enterprise AI strategy into an executable roadmap and feeding learnings back into the broader engineering organization. Key responsibilities include hiring, performance management, career development, roadmap ownership, operating cadence management, partnership with DevOps & AppSec and Cloud Engineering, executive reporting on key metrics (PoC velocity, Power Agents adoption, engineering hours saved, AI Standards compliance), managing the AI agent workforce lifecycle, fostering cross-organizational relationships, delivering major AI & Innovation initiatives, and partnering on Enterprise AI Standards with Legal, InfoSec, and Data Governance.

Requirements

8+ years of software engineering experience with a demonstrated track record of directly managing engineers.
Experience standing up, scaling, or leading an AI/ML, platform, or innovation-focused engineering function, ideally one operating with agentic AI, LLM-based systems, or rapid prototype-to-production delivery.
A track record of partnering with VP or executive-level leaders to translate strategy into an executable, resourced roadmap, and of making the prioritization calls when team capacity and stakeholder demand conflict.
Experience owning delivery metrics and KPIs and reporting them credibly to senior leadership on a recurring cadence.

Nice To Haves

Direct hands-on experience with agent frameworks, internal agent libraries (Power Agents or equivalent), or MCP/A2A-style integration patterns enough to have a credible technical conversation with a Principal AI Engineer.
Familiarity with enterprise data platforms (Snowflake) and cloud infrastructure (AWS), and with the DevOps/AppSec disciplines the team now partners with in place of a dedicated platform hire.
Existing JD Power relationships across Engineering Leaders, Product, Legal, InfoSec, or business unit leads – institutional knowledge compresses the path to full effectiveness in this role.
Experience leading teams that operate across both 0-to-1 prototyping and applied, production-facing delivery models simultaneously.

Responsibilities

Hire, manage, coach, and grow the AI & Innovation function; own performance management, career development, and org design decisions as the team scales.
Own the team roadmap: partner with the VP of Architecture to translate enterprise AI strategy into a quarterly roadmap for Innovation Crew (PoC delivery, Power Agents, AI Standards, Emerging Tech Radar) and Launch Lab (application delivery, hand-offs to maintaining teams); make the trade-off calls when demand exceeds capacity.
Own the operating cadence end to end: serve as final approver on the three-gate intake process, the escalation point when compliance or handoff issues stall a pilot, and the person who ensures the AI & Innovation process protects, rather than slows, engineering time.
Own the DevOps & AppSec and Cloud Engineering partnerships: establish and maintain the working relationship with DevOps & AppSec and Cloud Engineering so CI/CD, infrastructure, and application security needs for Innovation Crew and Launch Lab outputs are met without creating a bottleneck.
Own metrics and executive reporting: report PoC velocity, Power Agents adoption rate, engineering hours saved, and AI Standards compliance to the VP of Architecture and Engineering leadership; represent AI & Innovation results at Engineering Town Halls and quarterly business reviews.
Own the AI agent workforce lifecycle: set the standard for onboarding new agents into production, tracking their performance and adoption against Power Agents metrics, maturing agent capabilities as use cases evolve, and offboarding or retiring agents that no longer meet AI Standards or business need.
Own cross-org relationships: serve as the team's primary point of contact for the eight peer engineering clusters, Product, and business unit leaders; maintain the design-partner and consumer engagement model so demand is prioritized rather than triaged ad hoc; ensure OEM Solutions and Geography-based scope boundaries are respected.
Own delivery of major initiatives that intersect with AI & Innovation: AI Everywhere rollout, Agentic AI framework maturity, Snowflake AI/ML integration coordination with Internal Platforms, and the Engineering Metrics (DORA) program as it applies to the team.
Partner with Legal, InfoSec, and Data Governance on Enterprise AI Standards; ensure every initiative the team ships reflects current governance requirements before it reaches a business stakeholder.