Job Title: Senior AI Solutions Architect

12-month contract | Hybrid in the Greater Vancouver Metropolitan Area | Closing Date: July 6, 2026 | Must hold a valid Canadian Work Visa

Our client is seeking a highly experienced Senior AI Solutions Architect to lead the architecture and technical direction of enterprise AI initiatives focused on modernizing software delivery through AI-native development practices.

This is a senior, hands-on architecture role responsible for designing scalable AI-powered solutions, defining enterprise architecture standards, and establishing an AI-native Software Development Lifecycle (SDLC). Working closely with software engineers, architects, AI specialists, and business stakeholders, the successful candidate will guide the delivery of production-grade AI solutions while developing reusable frameworks, governance models, and engineering standards that can be adopted across the organization.

This opportunity is ideal for a technical leader who combines deep solution architecture expertise with current hands-on engineering experience across cloud-native development, large language models (LLMs), Retrieval-Augmented Generation (RAG), and modern AI application development on Microsoft Azure.

Responsibilities:

• Lead the end-to-end architecture and technical design of enterprise AI-native applications and application modernization initiatives
• Define and establish an AI-native Software Development Lifecycle (SDLC), including architecture standards, engineering playbooks, governance models, and reusable reference architectures
• Translate business objectives into scalable, secure, and production-ready AI solution architectures
• Design and develop reference implementations, prototypes, and proof-of-concepts using Azure, C#/.NET, Python, and modern AI technologies
• Architect enterprise Retrieval-Augmented Generation (RAG) solutions, vector search capabilities, embeddings, and AI knowledge retrieval frameworks
• Design and standardize agentic AI architectures and multi-agent orchestration patterns using modern AI frameworks
• Lead the selection, implementation, and operationalization of AI development toolchains, coding assistants, and developer productivity platforms
• Establish engineering standards for AI quality assurance, automated testing, security, governance, deployment pipelines, and production readiness
• Design observability, monitoring, tracing, and operational controls for enterprise AI applications
• Ensure AI solutions align with enterprise security, privacy, compliance, and responsible AI requirements
• Develop measurable success metrics demonstrating improvements in delivery speed, quality, automation, and engineering efficiency
• Produce architecture documentation, technical standards, governance artifacts, reference implementations, and reusable implementation templates
• Provide technical leadership, mentoring, code reviews, and architectural guidance to software engineers and cross-functional delivery teams
• Present architecture strategies, implementation approaches, and technical recommendations to senior leadership and key stakeholders

Qualifications:

Required Qualifications

• Undergraduate degree in Computer Science, Engineering, or another STEM discipline, or an equivalent combination of education and experience
• 12+ years of progressive experience in software engineering, solution architecture, and enterprise application delivery
• Proven experience designing, building, and deploying AI-powered enterprise applications using LLMs, RAG, and agentic AI architectures
• Strong hands-on development experience with Python and C#/.NET
• Experience designing cloud-native architectures on Microsoft Azure, including microservices, containers, CI/CD pipelines, and MLOps practices
• Experience developing AI applications using Azure OpenAI, OpenAI APIs, LangChain, Hugging Face, Semantic Kernel, LangGraph, AutoGen, CrewAI, or similar frameworks
• Experience designing vector search solutions using Azure AI Search, Cosmos DB, pgvector, Qdrant, or comparable technologies
• Experience defining engineering standards, architecture documentation, reference architectures, and technical governance frameworks
• Experience implementing AI testing, evaluation, regression testing, and quality assurance practices
• Strong understanding of APIs, Git, Agile software delivery, and modern engineering practices
• Excellent leadership, communication, stakeholder management, and technical mentoring skills

Preferred Qualifications

• Azure Solutions Architect Expert, AWS Solutions Architect, or comparable cloud architecture certification
• Experience with Azure OpenAI Service, Azure AI Studio, PromptFlow, Azure AI Evaluation SDK, DeepEval, or similar AI evaluation platforms
• Experience implementing AI observability using Azure Monitor, Application Insights, Dynatrace, LangSmith, MLflow Tracing, or OpenTelemetry
• Experience using GitHub Copilot, Cursor, or other AI-assisted software development tools within enterprise environments
• Experience with Infrastructure as Code using Terraform or Bicep
• Experience developing cloud-native applications using ASP.NET and .NET 8/10
• Experience working in highly regulated industries such as healthcare, insurance, financial services, or government

This is an exciting opportunity to define the future of AI-native software delivery within a large enterprise by establishing the architecture, engineering standards, and technical foundations that will drive next-generation AI application development.

NOTE: Interested candidates who meet the above qualifications are encouraged to apply directly. Due to the volume of applications, only those shortlisted will be contacted.