Enterprise AI Architect

Enterprise AI Architect (Contract, Remote, Canada)

Location: Remote (Canada)

Employment Type: Contract (6–12 months, extension possible)

About the Role

We're looking for an Enterprise AI Architect to work alongside our clients in-house AI Center of Excellence (CoE), under shared leadership. You'll act as a senior technical partner to the CoE, shaping the architecture, standards, and delivery of enterprise AI solutions from concept through production. You'll bring outside perspective and hands-on expertise to accelerate how we design, build, and deploy AI-driven processes at scale.

What You'll Do

• Define the enterprise AI reference architecture covering data, models, orchestration, security, and governance

• Partner with the AI CoE to evaluate use cases, prioritize initiatives, and translate business needs into technical solution designs

• Design and oversee development of AI solutions, including GenAI/LLM applications, RAG pipelines, agentic workflows, and ML models

• Establish MLOps/LLMOps practices for deployment, monitoring, versioning, and lifecycle management

• Evaluate and recommend AI platforms, foundation models, vector databases, and tooling (build vs. buy)

• Ensure AI solutions meet security, privacy, compliance, and Responsible AI standards (including Canadian requirements such as PIPEDA)

• Integrate AI capabilities into existing enterprise systems (ERP, CRM, data platforms, APIs)

• Create architecture documentation, design patterns, and reusable accelerators for the CoE

• Provide technical guidance and mentorship to CoE engineers, data scientists, and business stakeholders

• Present architecture decisions, roadmaps, and trade-offs to senior leadership

What You Bring

• 10+ years in solution/enterprise architecture, with 3+ years designing and delivering AI/ML solutions in production

• Hands-on experience with GenAI and LLMs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Google Vertex AI, or open-source models)

• Strong knowledge of RAG, vector databases, prompt engineering, agent frameworks, and evaluation methods

• Experience with a major cloud platform (Azure, AWS, or GCP) and cloud-native architecture

• Solid understanding of MLOps/LLMOps, CI/CD, containerization (Docker, Kubernetes), and infrastructure as code

• Proficiency in Python and familiarity with modern data engineering stacks (Snowflake, Databricks, Spark, etc.)

• Working knowledge of AI governance, model risk management, data privacy, and security best practices

• Excellent communication skills, with the ability to work with both technical teams and executives

• Proven ability to work independently and collaboratively with an internal team in a remote setting

Nice to Have

• Cloud or AI certifications (Azure AI Engineer, AWS ML Specialty, Google Professional ML Engineer, TOGAF)

• Experience setting up or advising an AI Center of Excellence

• Background in regulated industries (financial services, healthcare, insurance, public sector)

• Experience with enterprise automation platforms or agentic AI orchestration tools