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About the Role

The AI Platform Engineering Lead is the senior technical authority for how AI is built at AGF. This hands-on role defines AI solution blueprints, owns the platforms they run on, and provides the engineering environment, tooling, and guardrails for AI teams. The role connects AI workloads to governed enterprise data, ensuring deployed agents and models are identified, permissioned, monitored, and auditable. It involves significant coding, configuration, and architecture work, including designing reference implementations, building shared components, resolving integration issues, setting standards, mentoring engineers, evaluating platforms, and advising leadership.

Responsibilities

Define and maintain the reference architecture for AI and agentic solutions, 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 for engineering teams.
Establish platform and model selection criteria and make clear recommendations.
Maintain a forward-looking roadmap for AI platforms, assessing new capabilities, deprecations, and vendor direction.
Lead architecture and design reviews for AI solutions.
Set the target state for AI solution cost, performance, latency, and resilience, and design to it.
Own the technical configuration, evolution, and operational health of AGF's AI platforms.
Evaluate, pilot, and onboard new AI platforms, models, and tooling.
Manage model access, entitlements, quotas, regions, and data residency configuration.
Implement gateway, routing, caching, and rate-limiting patterns.
Establish cost transparency for AI consumption with monitoring, budgets, and alerting.
Provide observability for AI workloads: tracing, prompt and response logging, quality and drift monitoring, usage analytics, and incident diagnostics.
Own the engineer onboarding experience for AI development.
Design and operate the promotion process for AI assets through development, test, and production.
Implement CI/CD pipelines and infrastructure as code for AI workloads.
Define environment strategy, workspace structure, and separation of duties.
Ensure AI solutions meet enterprise standards for availability, monitoring, alerting, support handover, and disaster recovery.
Work with Technology Services operations teams to integrate deployed AI solutions into support 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 for moving prototypes to governed, production-grade data.
Implement agent governance and lifecycle management.
Provide expert technical guidance on complex projects.
Foster a culture of innovation and elevate the team's capabilities.
Act as the technical counterpart to the AI Engineers and run an AI engineering community of practice.
Build and lead a small AI platform engineering team as adoption scales.

Requirements

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.

Skills

Azure architecture and services, including Azure AI Foundry, Entra ID, networking, and key and secret management.
Databricks, including lakehouse architecture, Unity Catalog governance, jobs, and workflows.
Microsoft Copilot Studio and the Microsoft 365 and Power Platform extensibility model.
Anthropic Claude and other frontier model APIs, including their enterprise deployment and safety controls.
Azure DevOps, GitHub, CI/CD pipelines, infrastructure as code such as Terraform or Bicep, and modern DevOps practice.
Strong hands-on software engineering with advanced Python, and working knowledge of at least one additional language relevant to enterprise integration.
Agent frameworks and orchestration, tool and function calling, and multi-agent design patterns.
Experience with Microsoft SQL server and related database technology.
Retrieval-augmented generation, embeddings, vector search, and context engineering at enterprise scale.
Prompt engineering, model evaluation, and AI testing and observability tooling.
Application and data security architecture, including secrets management and data classification.
MLOps and LLMOps tooling, and model lifecycle management.
Knowledge graphs, semantic layers, and metadata management.
Containerized and cloud-native application delivery, including Kubernetes and serverless patterns.
FinOps practices applied to cloud and AI consumption.
Relevant certifications such as Azure Solutions Architect, Databricks Data Engineer or Architect.
Familiarity with investment management, trading, research, or client servicing platforms and data.
Microsoft Agent 365, Entra Agent ID, and Microsoft Purview.
Exceptional problem-solving and analytical abilities.
Strong stakeholder management and relationship-building skills.
Ability to influence and drive outcomes without direct authority.
Strong communication and presentation skills.
Product-oriented mindset focused on measurable business outcomes.
Curiosity, adaptability, and a passion for continuous learning.
Ability to operate effectively in ambiguous and rapidly evolving environments.
Sound judgment balancing innovation with governance, security, and risk considerations.

Location

Toronto, Canada

Work Type

Hybrid

Experience Level

Senior
Minimum 7 years of experience
Minimum 3 years of hands-on experience

Education Level

Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, Information Technology, or a related discipline.

Salary/Compensations

$130,000 – $180,000 annually

Benefits

Comprehensive and competitive total rewards package designed to support the success and well-being of our employees, which may include a combination of base salary, variable compensation, benefits, and retirement savings plans.

About the Company

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.
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.

Equal Opportunity

AGF is an equal opportunity employer committed to fostering an inclusive and accessible workplace. We welcome and encourage applications from individuals of all backgrounds, including women, Indigenous peoples, racialized persons, persons with disabilities, and members of the 2SLGBTQIA+ community.
We do not discriminate on the basis of race, national or ethnic origin, colour, religion, age, sex, sexual orientation, gender identity or expression, marital status, family status, disability, or any other status protected by applicable legislation.
We are committed to providing reasonable accommodations for applicants with disabilities throughout the recruitment process. If you require accommodation at any stage of the application or hiring process, please contact us at hr@agf.com so that appropriate arrangements can be made.