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 Qualified 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

📌 Enterprise AI Architect (Canada)
🏢 Gala Solutions
📍 Canada