Senior Software Engineer (AI)

**Job Title
: Senior AI Software Developer**

12-month contract | Hybrid, 3 days/week on-site in the Greater Vancouver Metropolitan Area | Must hold a valid Canadian Work Visa

Our leading public sector client is seeking a
Senior AI Software Developer
to lead the technical execution of AI-native software initiatives within a modern cloud environment.

This is a hands-on engineering role embedded within a cross-functional delivery team, responsible for designing, building, and deploying production-grade application rewrites using AI-native tools and techniques on the Azure platform.

The role will drive end-to-end delivery, from requirements intake through production deployment, while demonstrating how an AI-native Software Development Lifecycle (SDLC) can improve delivery velocity, automation, quality, and time-to-market. The successful candidate will help define engineering standards for AI-assisted development, operationalize modern AI development tooling, and create reusable playbooks and reference architectures for broader organizational adoption.

This opportunity is ideal for someone with a strong ownership mindset who is passionate about advancing AI-enabled engineering practices within enterprise environments.

Responsibilities:

AI-Native Application Development

• Design, build, and deploy production-grade applications and application rewrites using C#, ASP.NET, .NET 10, and Azure
• Implement monitoring, logging, observability, and operational readiness best practices across deployed solutions
• Integrate LLM and AI capabilities into enterprise applications using Azure OpenAI, OpenAI APIs, and open-source models
• Progress AI-enabled solutions from prototype through to production-ready deployment

AI Toolchain & Engineering Enablement

• Select, configure, and operationalize AI development tooling, including AI-assisted IDE integrations, coding assistants, code review tooling, and workflow automation
• Implement agentic AI frameworks and orchestration patterns using technologies such as Semantic Kernel, LangChain, LangGraph, CrewAI, AutoGen, and LlamaIndex
• Develop reusable orchestration workflows and AI-enabled engineering components
• Define and implement AI-native engineering standards, release processes, deployment controls, and governance practices

AI Evaluation, Observability & Quality Engineering

• Design and optimize RAG pipelines, embeddings, retrieval strategies, re-ranking, and vector storage solutions
• Implement prompt engineering strategies, memory management, prompt versioning, and task chaining methodologies
• Develop AI evaluation and testing frameworks including regression suites, automated quality gates, red-teaming, and safety validation
• Implement AI observability and tracing using Azure Monitor, Application Insights, LangSmith, MLflow Tracing, OpenTelemetry, and related platforms
• Integrate application quality and security controls including static analysis, dependency scanning, code quality checks, and AI-generated code review gates

Architecture, Governance & Delivery Leadership

• Develop an AI-Native SDLC Playbook documenting methodologies, standards, reusable templates, governance checkpoints, deployment controls, and lessons learned
• Define release management and deployment frameworks ensuring AI-enabled development operates within enterprise governance and compliance guardrails
• Produce measurable comparisons between AI-native delivery approaches and traditional SDLC models, including metrics around velocity, defect density, automation coverage, and cost efficiency
• Present pilot outcomes, quantified benefits, risks, and recommendations to technical and business stakeholders
• Mentor developers through code reviews, pairing sessions, and technical knowledge sharing

Qualifications:

Required Experience

• 8+ years of software development experience, including recent hands-on work with AI, LLMs, or AI-enabled application delivery
• Strong experience designing AI-enabled products and workflows involving LLMs, RAG, or agentic systems
• Proficiency in Python and experience with AI/ML frameworks such as OpenAI SDKs, LangChain, and Hugging Face
• Strong understanding of agent-based design concepts and orchestration frameworks including Semantic Kernel, LangChain, or AutoGen
• Experience with vector databases and retrieval systems including Cosmos DB, pgvector, Qdrant, or similar platforms
• Hands-on experience developing and executing AI evaluation frameworks, regression testing, and automated quality gates
• Strong experience with C#, .NET Core, ASP.NET, and object-oriented software development
• Experience designing and implementing cloud-native solutions within Azure environments
• Knowledge of APIs, CI/CD pipelines, Git workflows, Infrastructure as Code, and Agile delivery practices
• Ability to communicate complex AI concepts clearly to technical and non-technical audiences
• Strong collaboration and stakeholder engagement skills

Preferred Experience

• Experience with advanced multi-agent orchestration frameworks such as CrewAI, LangGraph, AutoGen Studio, or Semantic Kernel Agents
• Hands-on experience using AI-native development tools such as GitHub Copilot, Cursor, or similar AI-assisted engineering platforms in production environments
• Experience with AI evaluation and benchmarking platforms such as Azure AI Evaluation SDK or DeepEval
• Familiarity with AI observability and tracing tools including LangSmith, MLflow Tracing, Weights & Biases, and PromptFlow
• Experience with prompt management and versioning strategies
• Strong Azure platform experience including Azure App Service, Azure Functions, Container Apps, Azure SQL, Azure Key Vault, Azure DevOps, and Azure Monitor
• Experience with Terraform or other Infrastructure as Code frameworks
• Experience working within regulated industries such as healthcare, insurance, government, or financial services
• Demonstrated experience defining engineering standards, architecture decision records (ADRs), runbooks, playbooks, and reference architectures

Education & Certifications:

• Undergraduate degree in Computer Science, Engineering, Data Science, or related STEM discipline, or equivalent experience

Why This Role:

• Opportunity to shape enterprise-scale AI-native software delivery practices
• High-impact role focused on modern AI engineering, automation, and cloud-native development
• Exposure to advanced AI orchestration, evaluation, and observability frameworks
• Collaborative, innovation-focused environment driving next-generation software delivery capabilities

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.