GenAI Developer at Stantec contributing to enterprise AI systems and architectural guidance. Collaborating with data scientists and engineers to deliver scalable, secure solutions.
Responsibilities
Architect end-to-end GenAI solutions, including model lifecycle management, evaluation, deployment, and monitoring.
Partner with ML/AI leads and engineering teams to integrate LLMs, autonomous agents, and GenAI services into existing and new solution pipelines.
Act as a technical advisor and reviewer, supporting architectural decisions, code reviews, and design trade-offs.
Provide architectural guidance for production deployments using Azure-native services, Databricks, and Azure DevOps CI/CD pipelines, ensuring solutions align with enterprise standards.
Review and advise on infrastructure approaches, including containerization, orchestration, and infrastructure-as-code to ensure scalability, security, and operational readiness.
Collaborate with product owners, engineering, security, and data teams to design solutions that meet functional and non-functional requirements (performance, reliability, compliance, and cost).
Establish and enforce governance for model usage, prompt and tool management, safety controls, data handling, and lifecycle management.
Design integrations with enterprise data platforms, knowledge sources, and APIs, ensuring appropriate access controls and auditability.
Guide implementation teams through design reviews, technical decision-making, and delivery of best practices.
Document architectural patterns, methodologies, and lessons learned; contribute to internal knowledge bases and Communities of Practice.
Evaluate emerging GenAI technologies and recommend adoption strategies based on business value and risk.
Stay current with emerging research, tools, and frameworks in Generative AI, Agentic AI, and multi-agent systems.
Requirements
Strong background designing and delivering modern cloud solutions, APIs, and data/AI platforms.
Demonstrated experience with GenAI solution patterns
Familiarity with security, privacy, and governance practices for enterprise AI solutions.
Ability to communicate complex concepts clearly to technical and non-technical audiences, influencing stakeholders through architecture guidance.
Experience partnering across disciplines in agile delivery environments.
Understanding application deployment, hosting, and scaling using the Azure App Service platform within Azure environments.
Master’s degree or higher degree in Computer Science, Engineering, or related field (or an equivalent combination of education and experience).
7+ years of professional experience in architecture, software engineering, data engineering, or AI/ML solution delivery, with recent hands-on GenAI solution experience.
Experience deploying AI/GenAI solutions in Azure environments, including familiarity with Azure AI Foundry and Databricks Mosaic AI, would be highly valued.
Benefits
Health, dental, and vision plans
Wellness program
Health care spending account
Wellness spending account
Group registered retirement savings plan
Employee stock purchase program
Group tax-free savings account
Life and accidental death & dismemberment (AD&D) insurance
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