Main Activities: Define enterprise AI platform architecture and roadmap.

Design, build and operate AI-native CI/CD platforms.

Implement secure-by-design AI controls and governance.

Define reliability, observability, resilience and Fin

Ops practices.

Lead architecture reviews and developer enablement programs.

Provide technical leadership across engineering teams.

Knowledge/Skill Requirements: 7+ years of software, platform, or cloud engineering experience, with 3+ years in AI/ML platforms or agentic AI systems.

Deep hands-on expertise with Azure (AKS, networking, private endpoints, identity, Key Vault) and Azure AI Foundry or equivalent AI platforms.

Proven experience building CI/CD pipelines for ML/LLM workloads (model, prompt, and agent lifecycle management).

Solid background in distributed systems, container orchestration (Kubernetes), and API/SDK design.

Experience with agent frameworks (e.g., Semantic Kernel, Lang

Chain, Auto

Gen)



and orchestration patterns (memory, tools, planning).

Solid understanding of LLM inference optimization, model routing, evaluation, and observability.

Track record of establishing platform standards, paved paths, and developer enablement at scale.

Excellent collaboration and communication skills across engineering, security, risk, and business stakeholders.

Preferred Qualifications Prior experience in regulated industries (financial services, banking, insurance).

Familiarity with Microsoft Fabric, Power Platform, Copilot, and Copilot Studio integrations.

Experience with Fin

Ops for AI workloads including cost attribution, token accounting, and model economics.

Background in Responsible AI, model governance, and evaluation frameworks.

Contributions to open-source AI/agent platform projects.

📌 Staff AI Platform & Agent Runtime Engineer (Toronto)
🏢 Equitable Bank
📍 Toronto