Senior Manager, GenAI & Cognitive AI

Our Story &

Purpose:

We’re Vancity, a member‑owned credit union built on the principles of inclusion and social justice. Since 1946, our relentless commitment to these values has helped us challenge the status quo and break down barriers. We’ve made bold commitments to become net‑zero by 2040 across all mortgages and loans, and we’re actively pursuing strategies in Indigenous banking and financial resilience for our members.

As the largest private sector Living Wage Employer in Canada, we’re proud to be consistently recognized as one of the country’s Top Employers. If you’re ready to join our team of 2,300 diverse individuals, access competitive rewards and benefits, and be part of a greater movement - apply today!

As a Senior Manager, GenAI & Cognitive AI
, you will lead Vancity’s GenAI & Cognitive AI Pod, shaping our GenAI architecture, guiding delivery of LLM and agentic AI solutions, and building a high‑performing team that will help advance Vancity’s AI‑enabled transformation. You will oversee RAG architectures, GenAI platforms, agentic frameworks, experimentation environments, and cognitive automation patterns - partnering with leaders across AI, platform engineering, and the business to translate member and organizational needs into scalable, secure, production‑ready AI capabilities.

You’ll thrive in this role if you’re a hands‑on technical leader with strong architecture foundations, deep experience across Azure and Databricks, and a passion for coaching teams and enabling enterprise adoption of modern AI systems.

This is a Full ‑time, Permanent role based in Vancouver and will report directly to the Director, AI Centre of Excellence
. Our head office is based in Vancouver, but we are open to candidates in BC and Ontario. While this position is for an existing vacancy and provides a remote work arrangement, you will be expected to be on‑site for events and business demands.

• Leading the design, development, and deployment of Generative AI and agentic AI solutions
• Owning end‑to‑end delivery of LLM use cases from feasibility and PoC through production
• Overseeing RAG architectures, GenAI APIs, agent orchestration, and cognitive automation patterns
• Building and operationalizing experimentation and evaluation frameworks for accuracy measurement, benchmarking, and continuous improvement
• Defining and owning GenAI reference architectures across Azure and Databricks
• Establishing best practices for Azure OpenAI usage, RAG design, vector search, agent frameworks, and secure GenAI deployment
• Ensuring all GenAI solutions meet enterprise‑grade security, privacy, and governance requirements
• Leading and developing the GenAI & Cognitive AI Pod including engineers and conversational designers
• Providing coaching, mentorship, and technical leadership that strengthens engineering standards and team culture
• Partnering with AI leaders and cross‑functional stakeholders to shape and execute the GenAI roadmap

• Master’s or PhD in Computer Science, Software Engineering, or a related technical field
• 9-12 years of experience in AI, ML, data engineering, or software engineering roles
• 4+ years of hands‑on experience with Generative AI and agentic AI concepts including LLMs, RAG, and AI agent frameworks
• 3+ years of experience designing scalable cloud‑based AI architectures
• 2+ years working with Azure, including Azure AI Foundry or related services
• Demonstrated experience deploying AI/ML models into production environments
• Strong technical fluency in LLM ecosystems, RAG patterns, NLP, CLU, and modern agentic AI architectures
• Proficiency in Databricks for data engineering, ML workflows, or GenAI pipelines
• Familiarity with CI/CD, MLOps, cloud‑native deployment practices, and secure enterprise AI patterns
• Proven people leadership experience including coaching, mentorship, and performance management
• Strong communication and stakeholder management skills with the ability to operate in ambiguity

• Experience integrating GenAI solutions with RPA or automation platforms
• Knowledge of Responsible AI, model risk management, or AI…