Job Title:, 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

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📌 Enterprise AI Architect (Manitoba)
🏢 GALA SOLUTIONS
📍 Manitoba