AI Developer (Edmonton)
Deloitte View all jobs
- Edmonton, AB
- $80,000-138,000 per year
- Permanent
- Full-time
Work Model: Hybrid
Reference code: 132440
Primary Location: Edmonton, AB
All Available Locations: Edmonton, ABOur PurposeAt Deloitte, our Purpose is to make an impact that matters. We exist to inspire and help our people, organizations, communities, and countries to thrive by building a better future. Our work underpins a prosperous society where people can find meaning and opportunity. It builds consumer and business confidence, empowers organizations to find imaginative ways of deploying capital, enables fair, trusted, and functioning social and economic institutions, and allows our friends, families, and communities to enjoy the quality of life that comes with a sustainable future. And as the largest 100% Canadian-owned and operated professional services firm in our country, we are proud to work alongside our clients to make a positive impact for all Canadians.By living our Purpose, we will make an impact that matters.
- Have many careers in one Firm.
- Enjoy flexible, proactive, and practical benefits that foster a culture of well-being and connectedness.
- Learn from deep subject matter experts through mentoring and on the job coaching
- 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