AI Platform Engineering Lead

About AGF: Founded in 1957, AGF Management Limited (AGF) is an independent and globally diverse asset management firm. Our companies deliver excellence in investing in the public and private markets through three business lines: AGF Investments, AGF Capital Partners and AGF Private Wealth. AGF brings a disciplined approach, focused on incorporating sound, responsible and sustainable corporate practices. The firm’s collective investment expertise, driven by its fundamental, quantitative and alternative investing capabilities, extends globally to a wide range of clients, from financial advisors and their clients to high-net worth and institutional investors including pension plans, corporate plans, sovereign wealth funds, endowments and foundations. Headquartered in Toronto, Canada, AGF has investment operations and client servicing teams on the ground in North America and Europe. AGF serves more than 820,000 investors. AGF trades on the Toronto Stock Exchange under the symbol AGF.B. About the Team: AGF is building an enterprise-wide Artificial Intelligence capability to improve client outcomes, investment performance, operational effectiveness, and employee productivity. Through its AI Centre of Expertise (AI CoE), AGF is establishing the governance, technology, talent, and operating model needed to responsibly scale AI across the organization. As part of this strategy, AGF is creating a team of Forward Deployed AI Engineers who will work at the intersection of business strategy, technology, and AI innovation to identify, build, and deploy solutions that create measurable business value. Initial priorities will focus on Investment Management and Distribution, with expansion across all business functions over time. About the Role: The AI Platform Engineering Lead is the senior technical authority for how AI is built at AGF. Reporting to the VP, Technology Services, the role defines the blueprints that AI solutions follow, owns the platforms those solutions run on, and provides the engineering environment, tooling, and guardrails that allow AI teams to move quickly without compromising security, cost control, or compliance. The role works closely with AI Forward Deployed Engineers and other technical teams to connect AI workloads to governed enterprise data, ensuring every deployed agent and model is identified, permissioned, monitored, and auditable. Platform scope include but are not limited to Databricks, Microsoft Copilot Studio, Azure AI Foundry, Anthropic Claude, and Microsoft Agent 365. This is a hands-on role. The successful candidate will spend meaningful time in code, configuration, and architecture, designing reference implementations, building the first version of shared components, and resolving integration and access issues, while also setting standards, mentoring other engineers, evaluating platforms, and advising senior leadership. It is a senior role carrying technical leadership responsibility, intended for an engineer-architect who is energized by building a new capability from a blank page and who is comfortable making decisions with incomplete information in a fast-moving technology landscape. Why Join AGF? This is a unique opportunity to help shape AGF's AI future from the ground up. You will have the opportunity to influence strategy, drive business outcomes, build enterprise-scale solutions, and help establish AI as a core capability across AGF. Your Responsibilities: AI Architecture & Blueprints: • Define and maintain the reference architecture for AI and agentic solutions at AGF, covering agent design patterns, retrieval-augmented generation, orchestration, memory and state, tool and API access, model selection, and human-in-the-loop controls. • Produce blueprints, reference implementations, and decision guides that engineering teams can apply directly, rather than architecture documents that require interpretation. • Establish platform and model selection criteria, and make clear recommendations on where each platform is the right choice and where it is not. • Maintain a forward-looking roadmap for AI platforms, assessing new capabilities, deprecations, and vendor direction, and translating them into a practical plan for AGF. • Lead architecture and design reviews for AI solutions built by the AI Engineers and business teams. • Set the target state for AI solution cost, performance, latency, and resilience, and design to it. AI Platform Ownership & Engineering: • Own the technical configuration, evolution, and operational health of AGF's AI platforms, including Databricks, Azure AI Foundry, Microsoft Copilot Studio, and Anthropic Claude. • Evaluate, pilot, and onboard new AI platforms, models, and tooling across commercial, hosted, and open-source options. • Manage model access, entitlements, quotas, regions, and data residency configuration across providers. • Implement gateway, routing, caching, and rate-limiting patterns that control consumption cost and give engineers a consistent interface to model providers. • Establish cost transparency for AI consumption, with monitoring, budgets, and alerting by team and by use case. • Provide observability for AI workloads: tracing, prompt and response logging, quality and drift monitoring, usage analytics, and incident diagnostics. • Own the engineer onboarding experience so that a new developer can be productive in days rather than weeks. • Design and operate the promotion process for AI assets, including prompts, agents, models, indexes, notebooks, and applications, through development, test, and production. • Implement CI/CD pipelines and infrastructure as code for AI workloads, with automated testing, approval gates, and rollback. • Define environment strategy, workspace structure, and separation of duties consistent with AGF's change management and audit requirements. • Ensure AI solutions meet enterprise standards for availability, monitoring, alerting, support handover, and disaster recovery. • Work with Technology Services operations teams to bring deployed AI solutions into established support and incident management processes. • Define how AI workloads consume governed data, including lakehouse patterns, Unity Catalog governance, vector and feature stores, embedding pipelines, and lineage. • Provide the engineering path that moves a promising prototype onto governed, production-grade data. • Implement agent governance and lifecycle management covering registration, ownership, entitlement, monitoring, retention, and decommissioning • Provide expert technical guidance on complex projects, foster a culture of innovation, and elevate the team's capabilities in building robust AI solutions. • Act as the technical counterpart to the AI Engineers, run an AI engineering community of practice. • Build and lead a small AI platform engineering team as adoption scales. Your Qualifications: • Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, Information Technology, or a related discipline. • Minimum 7 years of experience in software engineering, platform engineering, data engineering, or solution architecture • Minimum 3 years of hands-on experience designing and delivering generative AI, agentic, or machine learning solutions • Demonstrated ownership of a shared engineering platform or developer environment used by multiple teams. • Experience establishing engineering standards, CI/CD, and release governance in a regulated or audited environment. • Track record of building a capability from the ground up, including tooling selection, vendor evaluation, and first-of-kind implementations. • Experience partnering with security, risk, and compliance functions to bring new technology into controlled production use. • Experience operating in fast-paced environments with evolving priorities. • Financial services, investment management, wealth management, or capital markets experience is considered a strong asset. Technical