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AtkinsRéalis

Engineering services for infrastructure and energy

Director – Artificial Intelligence - Finance

Business OperationsConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • A degree in Finance, Business, Technology, Engineering or a related discipline, or equivalent relevant experience, is expected.
  • Significant experience leading AI, data, automation or digital transformation in a complex organization, with demonstrated outcomes beyond proofs of concept.
  • Experience navigating architecture, cybersecurity, privacy, data governance and risk requirements while maintaining business value and delivery pace.
  • Practical experience with Copilot Cowork or Claude Cowork, including a record of deploying agentic workflows and demonstrating value in another organization.
  • Hands-on experience building, testing and deploying AI agents, preferably in Microsoft Copilot Studio, with examples personally created or materially developed.
  • Experience in an engineering, professional-services or project-based business; familiarity with enterprise Finance platforms, including Oracle-based environments.
  • Working knowledge of generative AI, agents, analytics and intelligent automation sufficient to build focused solutions and challenge complex technical designs.
  • Strong understanding of Finance processes and decisions, ideally including FP&A, reporting, project or contract performance, working capital and financial controls.
  • Evidence of moving solutions beyond demonstrations to adoption, changed workflows and measurable business outcomes.
  • Active, capable use of Microsoft Copilot, ChatGPT or Claude in day-to-day professional work, with sound judgment about approved tools, sensitive information and human review.
  • Ability to build investment cases, evaluate total cost and alternatives, establish benefit baselines and demonstrate return on investment.

Responsibilities

  • Define and communicate a value-first AI strategy and roadmap for Global Finance aligned with Finance priorities, enterprise AI strategy, technology standards and the Financial Systems roadmap.
  • Determine where AI can materially improve outcomes, where conventional automation or process redesign is preferable, and where an opportunity should not proceed.
  • Build a shared agenda across FP&A, Controllership, Project Finance and other Finance teams, and engage regional and business leaders to identify scalable needs.
  • Advise Finance leadership on investment choices, dependencies and risks; secure sponsorship and rally teams that do not report to the Director.
  • Establish transparent use-case intake and prioritization connected to enterprise channels and governance; assess business value, process and data readiness, feasibility, adoption, total cost and risk.
  • Maintain a sequenced portfolio with named sponsors, accountable process owners, delivery partners, milestones and clear decisions to proceed, change direction or stop.
  • Prioritize opportunities with a credible path to impact over numerous pilots, assessing each candidate use case through its own business case.
  • Require proportionate business cases before material investment, including baselines, expected benefits, implementation and ongoing costs, risks, dependencies, adoption assumptions and alternatives.
  • Distinguish time saved from capacity genuinely redeployed and from cost removed, and do not treat them as interchangeable financial benefits.
  • Agree measurement methods and benefit owners before delivery; track investment and realized value at use-case and portfolio levels, with independent validation where appropriate.
  • Report candidly on adoption, net value, cost and control effectiveness; recommend whether to improve, scale or discontinue underperforming initiatives.
  • Personally design, build and refine selected Finance agents and AI-enabled workflows, especially early prototypes and focused solutions that accelerate learning.
  • Use Microsoft Copilot and Copilot Studio to configure agents, test them with users, assess reliability and improve outputs based on feedback.
  • Use AI tools regularly in professional work to improve analysis, research, drafting and workflow execution while applying appropriate review and data-handling requirements.
  • Turn Finance problems into working demonstrations, assess limitations and costs, and decide whether solutions should stop, improve or enter the approved production route.
  • Stay close enough to delivery to challenge designs, troubleshoot barriers and coach builders, while partnering with Digital and IT on supported deployment rather than serving as sole developer of enterprise-scale products.
  • Translate enterprise AI policy and standards into a Finance operating model covering ownership, intake, risk assessment, testing, approvals, human oversight, monitoring and lifecycle management.
  • Partner with Digital, IT, the Chief Digital Officer’s organization, Cybersecurity, Privacy, Legal, Risk and Internal Audit to clarify decision rights and navigate approval for production use.
  • Protect sensitive Finance and client information through appropriate access, validation, traceability and human review before AI outputs inform reporting or decisions.
  • Work with data and process owners on source quality, definitions and controls; reuse approved enterprise platforms and challenge unnecessary complexity without bypassing security or technology accountabilities.
  • Partner with the Financial Systems CoE so initiatives fit ERP, EPM and reporting architecture without creating competing technology roadmaps.
  • Agree delivery responsibilities with Digital and IT while retaining Finance accountability for business outcomes; redesign workflows with process owners around human decisions, exceptions and controls.
  • Lead communications, training and feedback to build user confidence, and create reusable approaches that scale across regions while respecting genuine process and risk differences.
  • Build and coach a small team with commercial judgment, hands-on capability and delivery discipline; mobilize a federated network of Finance champions, process owners and enterprise specialists.
  • Create a culture of curiosity, constructive challenge, accountability and collaboration, including confidence to recommend not using AI when appropriate.
  • Represent Finance in enterprise AI forums and lead by example as sponsor and practitioner by demonstrating tools, sharing what works and acknowledging limitations.

About the Company

AtkinsRéalis

Engineering services for infrastructure and energy

AtkinsRéalis provides engineering services for infrastructure and nuclear projects, connecting people, data, and technology to plan, design, build, and manage systems worldwide. It delivers integrated services through consulting, design, engineering, and project management, using a global team and data-driven collaboration to move projects from concept to commissioning. The company’s global reach and end-to-end capability across conventional engineering and nuclear sectors enable coordinated delivery across multiple disciplines. Its goal is to transform infrastructure and energy systems worldwide by delivering safe, reliable, and efficient engineering solutions.

Company size
10,001+
Company stage
Acquired
Total funding
$2.8B
Headquarters
Epsom, United Kingdom
Founded
1938

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