Technology Delivery Lead (Enterprise AI)

Location: Hybrid work in Toronto, Ontario, Canada; St. Louis, Indianapolis, Kansas City, Pittsburgh, or Louisville in the United States. At least three days per week in the local office or onsite with clients.

Company

hirify.global is a global professional services company advising clients on risk, reinsurance and capital, people and investments, and management consulting across 130 countries.

What you will do

• Define and execute product vision, strategy, multi-quarter roadmaps, requirements, delivery plans, success metrics, and business outcomes for enterprise AI solutions.
• Partner with engineers, architects, analysts, and business stakeholders on model development, data pipelines, APIs, cloud platforms, and AI infrastructure.
• Lead rapid AI proof-of-concepts by framing business problems, assessing data readiness, defining evaluations, and recommending next steps.
• Drive cross-functional delivery, managing risks, dependencies, trade-offs, vendor deliverables, and delivery cadence.
• Embed responsible AI practices covering traceability, privacy, bias, fairness, quality, and governance throughout the product lifecycle.
• Monitor KPIs, OKRs, adoption and product-health metrics, communicate value propositions and business cases, and present outcomes to executive leadership.

Requirements

• 5–8+ years of experience as a Technology Product Manager, Technology Delivery Lead, or in a similar role, including at least two years with AI, machine learning, or data-intensive products.
• Demonstrated success defining and executing product strategy in complex, fast-moving, cross-functional technology environments.
• Strong technical foundation in APIs, cloud platforms such as AWS, Azure, or GCP, data architecture, and system design.
• Experience partnering directly with engineers, architects, and technical teams in an agile product development environment.
• Proven ability to deliver enterprise-grade software products from concept through launch, adoption, and ongoing iteration.
• Exceptional written and verbal communication skills, with the ability to influence stakeholders and drive decisions without direct authority.

Nice to have

• Experience in portfolio delivery, a program management office, or a similar structure in a large organization.
• Familiarity with large language models, generative AI, natural language processing, computer vision, or other advanced AI technologies.
• Background in software engineering, data science, systems architecture, or a related technical discipline.
• Experience with enterprise AI governance, model risk management, responsible AI frameworks, or related controls.
• Experience with MLOps tools such as MLflow, Kubeflow, Amazon SageMaker, Azure Machine Learning, or equivalent platforms.
• An MBA or advanced degree in computer science, engineering, data science, or a related technical field.

Culture & Benefits

• Professional development opportunities, interesting work, and supportive leaders.
• Inclusive, collaborative environment focused on creating solutions with impact for colleagues, clients, and communities.
• Hybrid work model combining remote flexibility with office collaboration, connections, and professional development.
• Benefits and rewards intended to support employee well-being.