Engineering Manager, Forward Deployed Engineering
- Remote
- All customer & support jobs
- Ontario
- Full-Time
- Engineering
About the role
A little bit about our team:
WMG Technology’s Forward Deployed Engineering (FDE) team sits at the intersection of enterprise engineering and business enablement. We embed engineers with global business units — including Finance, HR, and our recorded music labels — to turn operational pain points into high-value AI and automation solutions.
Working directly with the business, we run a centralized intake, routing, and delivery model so the business can move in days or weeks using existing tools, while larger foundational work graduates cleanly onto the product roadmap. We set a shared technical bar, reuse what already works, and keep AI deployments secure, cost-transparent, and maintainable.
Your role:
Reporting to the Director of FDE & AI Optimization, the Engineering Manager will lead a team of embedded engineers and own how FDE work is taken in, built, reused, and graduated.
This is a hands-on people-manager role. You will coach engineers who sit inside lines of business while holding a centralized technical reporting structure, operating playbook, and delivery standard. You will partner with Data Engineer, Product Owner, and business sponsors to turn ambiguous requests into a clear, repeatable operating model — and to make sure FDE is a trusted path for AI optimization, not a shadow-IT queue.
The ideal manager brings an equal blend of technical judgment and organizational empathy: comfortable in the tools, rigorous about routing and reuse, and able to help non-technical stakeholders translate operational pain points into work the team can actually ship.
Here you’ll get to:
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Build, coach, and manage a high-performing FDE team, including hiring, performance, and embedding engineers in specific lines of business while keeping them aligned to core tech standards.
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Define, scale, and maintain the FDE technical operating playbook — intake standards, routing rules, reusable delivery models, and engagement lifecycle — so work enters, ships, and leaves FDE by clear criteria.
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Turn ambiguous organizational processes (intake routing, priority rubrics, and graduation gateways) into clear, repeatable frameworks that business sponsors actually use.
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Align engineers, product owners, business sponsors, and executive partners around shared technical standards, priority, and delivery roadmaps — and resolve boundary conflicts so there is one intake path, not shadow requests.
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Champion reusable assets, developer tooling (including ADK/SDK patterns and an internal assets marketplace), and best practices so teams stop reinventing the wheel and production work has a named owner and a maintenance path.
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Set the technical bar for bottom-up AI optimization: agents and automation on validated enterprise frameworks (including Databricks, Gemini Enterprise, Claude, and Airtable).
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Own end-to-end operational governance for FDE deliveries — security and compliance, Cost of AI telemetry, and lifecycle management from prototype through production graduation or retire.
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Partner with divisional leaders and budget owners to translate operational pain points into technical requirements, educate business units on how to work with tech, and give leadership a clear view of FDE capacity, outcomes, and aggregate AI cost.
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Define success metrics for the FDE engagement model and run the operating rhythm (intake SLA, reuse, outcomes) that keeps the team efficient as demand scales.
About you:
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You have 7+ years of experience in software engineering, solution architecture, data engineering, or AI/ML delivery, including 2+ years managing engineers.
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You have led teams in a Forward Deployed Engineering, technical consulting, or heavily matrixed environment where talent is embedded in the business and still held to a central technical bar.
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You have defined, scaled, and maintained operational playbooks — intake standards, routing, and reusable delivery models — not just written a process doc.
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You can transform ambiguous processes (intake routing, priority rubrics, graduation gateways) into clear, repeatable frameworks that stick across teams.
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You have championed reusable assets, developer tooling (e.g. ADK/SDK patterns), and best practices that improve team-wide efficiency and long-term asset maintenance.
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You have owned operational governance across the delivery lifecycle, including compliance, cost telemetry (Cost of AI), and the path from prototype to production graduation.
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You have deep familiarity with modern LLM ecosystems, agentic workflows, and cloud data platforms (e.g. Databricks, Gemini, Claude, Cursor).
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You can evaluate business requests with discernment — distinguishing agile, low-effort optimization wins (days/weeks) from intensive initiatives that belong on a product roadmap (months/years).
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You have exceptional written and verbal communication skills, with the ability to simplify complex AI paradigms into tangible operational value for non-technical stakeholders.
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You have experience measuring engineering ROI and managing vendor/licensing or infrastructure cost in a production environment.
We’d love it if you also had:
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Experience rolling out an intake + routing model in a matrixed enterprise (what the team takes vs. routes to product, platform, or decline), with a visible backlog and an SLA on triage.
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Hands-on delivery of agents, automation, or internal platforms on Databricks, Gemini Enterprise, Claude, Airtable, and/or Cursor.
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Experience standing up a reuse path (starter kits, ADK/SDK, asset marketplace) and a written production-ownership / graduate-or-retire standard.
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Music, media, or entertainment industry experience, or prior work supporting functions such as Finance, HR, or creative/label operations.
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Comfort operating as a player-coach: close enough to the technical work to set standards, without needing to be the strongest coder on the team.
Description as published by Warner Music Group.