Senior AI developer enhancing Quest’s on - premises enterprise software with C#/.NET, C++, and AI coding agents. Championing secure agentic workflows, testing, and developer productivity across Agile teams.
About the role
- Lead engineer building secure GenAI platforms, RAG pipelines, and enterprise applications for Vancity, a member-owned Canadian credit union. Leading production delivery, integrations, governance, and engineering standards.
Responsibilities
- Lead end-to-end delivery of secure Generative AI and agentic AI solutions from discovery and prototyping through production deployment, stabilization, and support
- Translate ambiguous business needs into measurable requirements, technical designs, thin vertical slices, and scalable solutions
- Build production-grade Python services, APIs, RAG pipelines, agent workflows, enterprise integrations, and reusable libraries
- Develop secure, accessible React and TypeScript applications supporting enterprise AI workflows, including human review, evidence, approvals, and exception handling
- Integrate AI services with enterprise data, APIs, systems of record, workflow platforms, identity, and approved tools or connectors
- Implement secure CI/CD pipelines, infrastructure as code, observability, controlled release management, rollback, and production-support practices
- Establish evaluation frameworks, representative test datasets, automated tests, engineering quality gates, and operational monitoring
- Embed privacy, governance, security, risk management, and Responsible AI controls into solutions
- Create reusable libraries, SDKs, templates, connectors, UI components, project structures, and delivery patterns
- Provide code-level leadership through mentoring, technical design guidance, code reviews, and hands-on troubleshooting
- Diagnose and resolve failures across models, retrieval, agents, tools, data, APIs, user interfaces, identity, infrastructure, and downstream systems
- Coordinate cross-functional dependencies and support operational readiness, knowledge transfer, and sustainable handover
- Report directly to the Senior Manager, Generative and Cognitive AI
Requirements
- Bachelor’s degree in computer science, Software Engineering, Data Science, Information Technology, or a related discipline, or an equivalent combination of education and relevant experience
- Minimum 8 years of progressive experience in software engineering, full-stack development, machine learning engineering, or AI solution delivery
- Deep, recent hands-on experience building, integrating, deploying, and supporting production GenAI, RAG, agentic AI, or intelligent automation systems
- Advanced experience building production-grade Python applications, APIs, asynchronous services, and distributed systems
- Strong software design, testing, and debugging skills
- Strong experience developing secure, accessible front-end applications using React, TypeScript, and related frameworks
- Hands-on experience with Azure cloud technologies, Azure OpenAI, Azure AI Search, Microsoft Foundry, Databricks, or comparable AI platforms
- Experience designing and implementing RAG pipelines, context engineering, structured generation, agentic workflows, secure tool integrations, and enterprise AI solutions
- Strong SQL and production data-engineering capability, including data profiling, transformation, quality validation, schema evolution, lineage, and reliable batch or event-driven pipelines
- Experience integrating AI services with enterprise data, APIs, application systems, and workflow platforms
- Strong knowledge of DevOps, CI/CD, infrastructure as code, containers, identity, observability, application monitoring, resilience, and controlled release practices
- Experience designing repeatable evaluation and regression methods for AI quality, safety, task success, and operational performance
- Experience leading technical delivery while remaining a substantial hands-on contributor, providing mentorship, and establishing engineering standards and best practices
- Knowledge of secure coding, Responsible AI principles, privacy controls, data governance, and enterprise risk requirements
- Ability to work directly with business users, domain experts, engineers, data and infrastructure teams, architecture, and control functions
- Clear written and verbal communication
- Experience deploying Large Language Models, agent frameworks, and advanced Generative AI applications in enterprise environments
- Experience with intelligent document processing, multimodal AI, high-volume document workflows, or human-in-the-loop reviewer solutions
- Experience with Microsoft Foundry, Azure OpenAI, Azure AI Search, MLflow, Unity Catalog, and Databricks AI capabilities
- Experience with enterprise API management, event-driven integration, workflow automation, and approved MCP-based tools or connectors
- Experience implementing GenAIOps, LLMOps, AgentOps, or MLOps capabilities across multiple environments
- Experience with containerization technologies, Kubernetes, cloud-native architectures, and platform engineering
- Experience working in financial services, another regulated industry, or an environment handling sensitive information
- Relevant certifications in Azure, Databricks, cloud architecture, AI engineering, security, DevOps, or software development disciplines
Benefits
- Competitive rewards and benefits
- Customizable flexible benefit packages for permanent employees
- 3–4 weeks of vacation per year initially, with additional days earned over time
- 2 extra statutory holidays in addition to BC’s 11 statutory holidays
- Care days for personal or family illness
- Health and dental benefits from the hire date, with three coverage levels
- Defined benefit pension providing guaranteed income for life
- Inclusive hiring and career development programs for Indigenous, Black, or Trans candidates
- Accessible, barrier-free recruitment experience and accommodations/support during the recruitment process
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