AI Developer (Edmonton)

• Design AI systems that automate complex knowledge workflows, replacing manual review, research, and compliance processes.
• Build AI-powered tools that evaluate large document sets against structured requirements, policies, and regulatory standards.
• Develop multi-agent LLM workflows that replicate analyst reasoning, incorporate internal methodologies, and accelerate decision-making processes.
• Deploy and scale enterprise-grade RAG and agentic chatbot systems that securely search internal knowledge bases, structured databases, and document repositories.
• Evaluate and benchmark foundation models (e.g., OpenAI, Gemini, Claude) to determine optimal trade-offs between performance, cost, and security.
• Implement AI governance practices including model evaluation, monitoring, cost tracking, and risk mitigation strategies.
• Build executive-facing dashboards that measure AI system accuracy, ROI, usage, and cost-per-query to inform leadership decisions.
• Engineer scalable cloud-native architectures using serverless and containerized patterns for high availability and cost efficiency.
• Design and maintain ETL/ELT pipelines and event-driven workflows to support AI applications with clean, reliable data.
• Collaborate with product owners, analysts, and technical stakeholders to translate complex business requirements into deployable AI systems.
• Ensure systems meet strict enterprise security, compliance, and data privacy standards.

• “Big Picture” thinker, with the ability to achieve excellence through effective delegation and though leadership
• Entrepreneurial attitude, desire to create new business, ability to inspire followership amongst team members
• Strong organization skills: ability to prioritize work demands, and meet deadlines

• Completed Undergraduate degree in a Business/Management/Analytics or related field
• MBA, Master's or PhD degrees and any recognized professional certifications would be an asset
• 3+ years building production-grade AI or data systems in enterprise or consulting environments.
• Strong Python engineering skills with experience building APIs and scalable backend services.
• Hands-on experience designing and deploying Retrieval-Augmented Generation (RAG) systems.
• Experience building multi-agent workflows using orchestration frameworks.
• Strong understanding of AI system evaluation, benchmarking, and cost optimization.
• Experience training/fine-tuning machine learning models
• Experience working in regulated environments where compliance, governance, and security are critical.
• Experience architecting solutions in Azure or other major cloud providers using serverless and container-based patterns.
• Familiarity with CI/CD, infrastructure-as-code, and production deployment best practices.
• Ability to communicate technical trade-offs clearly to executives and non-technical stakeholders.
• Experience designing systems that balance model capability with enterprise security constraints.

• Nice to have- eligible for a Canadian Federal Security clearance at least at an Enhanced Reliability level
• Python, Django or similar backend frameworks
• LangChain, LangGraph, MCP, or comparable LLM orchestration frameworks
• REST API design and microservices architectures
• Azure, AWS, GCP, or equivalent cloud services
• Docker and containerized deployments
• Terraform or other Infrastructure-as-Code tools
• CI/CD automation pipelines
• Experience working with OpenAI, Gemini, Claude, or other enterprise LLM providers
• Experience building monitoring dashboards and analytics tooling for AI systems

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• "careerSiteCompanyId" is used to send the request to the correct data center
• "JSESSIONID" is placed on the visitor's device during the session so the server can identify the visitor
• "Load balancer cookie" (actual cookie name may vary) prevents a visitor from bouncing from one instance to another

Deloitte