AI Builder- Manager

KPMG•Vancouver, BC

2d•Onsite

About The Position

At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference. KPMG in Canada is scaling an internal team of AI Builders who operate as the engine embedded in the business—powering the firm’s agent builds and transforming our business. This team is for people who sit at the intersection of enterprise operations, technology, and design, and who can look at how the firm works today, imagine how it should operate with agentic AI, and make that future real through execution. Our objective is to move beyond experimentation and enable real internal adoption of agentic AI, redesigning core workflows, decision systems, and operating models using autonomous agents that power KPMG’s service lines and internal teams. Within this role, AI Builders take ownership of the full build lifecycle, working closely with Engineering and Internal Transformation teams to move solutions from our KPMG AI Lab into scalable, reliable production systems, all within a complex and regulated enterprise.

Requirements

Typically with 5–8+ years of work experience, who can lead, build, and scale AI solutions in complex and regulated environment.
Strong enterprise fluency and understand how large organizations operate across functions, balancing strategy, technology, and execution.
Ability to navigate stakeholder landscapes and translate business needs into scalable AI-driven solutions.
Identify high-impact opportunities for agentic AI, connecting business pain points to practical, value-driven implementations.
Guide teams in prioritizing use cases that deliver measurable outcomes.
Think in systems and workflows, not just models, designing and overseeing multi-step processes that incorporate human-AI collaboration, governance boundaries, and appropriate levels of autonomy.
Lead with a builder mindset, empowering teams to move from concept to execution. Whether through code, low-code platforms, APIs, or orchestration tools, ensure solutions are tangible, usable, and production-ready.
Take end-to-end ownership at scale, from shaping problem statements and solution design through to deployment, adoption, and continuous improvement across client environments.
Comfortable operating in ambiguity and leading through it, guiding teams and clients through evolving problem spaces while maintaining momentum and clarity on outcomes.
Build, test, and iterate with intention, applying structured thinking while enabling speed.
Make informed trade-offs and coach others to do the same.
Embed responsible AI practices by design, ensuring that risk, governance, ethics, and trust are integral to every solution—not afterthoughts.
Lead and develop teams, creating an environment where builders can do their best work, grow quickly, and deliver meaningful impact for clients.
Submit your application with your CV that includes a hyperlink to a prototype portfolio. This can include a link to a hosting platform with examples of AI solutions, tools, experiments, or projects that demonstrate how you approach problem-solving and build with AI.

Nice To Haves

Something you’ve built - A project, a prototype, a system, a workflow you redesigned, an agent you configured, an automation you created. It doesn’t have to be agentic AI specifically. It just has to show us how you think and what you’re capable of. A GitHub repo, a demo video, a write-up of how you approached a hard problem, all work. We encourage thoughtful, original work—use AI as a tool, but make sure your own thinking and approach come through clearly.

Responsibilities

Lead the design, build, and deployment of production grade agents, plugins, skills, and tools using the firm’s approved AI and engineering stack.
Own the full build lifecycle: Lab prototyping, evaluations, productionization, change management, and ongoing product ownership.
Partner with cloud platform and engineering teams to ensure code quality, reliability, security, and scalability in production environments.
Ensure demo readiness, including narrative, artifacts, and appropriate demo safety and governance checks.
Package validated prototypes into reusable demos, kits, and handoff materials for downstream teams.
Balance speed with judgment, embedding risk, governance, and trust considerations appropriate to prototype maturity.
Provide delivery and technical leadership to Consultants and Senior Consultants, setting direction, reviewing work, and coaching teams.
Capture and share learnings through one pagers, replication kits, and internal AI literacy artifacts.