AI Architect designing and delivering intelligent AI applications for enterprise clients. Working with teams to develop scalable, production-grade solutions for complex challenges.
Responsibilities
Architect and develop production-grade agentic AI applications using modern agent frameworks and orchestration tools
Design and implement tool calling/function calling patterns that integrate LLMs with LOB APIs, databases, enterprise applications, and external services
Lead LLM application architecture decisions, including prompt engineering, context management, RAG pipelines, vectorization, embeddings, and model evaluation
Manage memory and state in complex agentic systems across multi-turn, multi-agent workflows
Build and maintain scalable cloud infrastructure on Azure, AWS, or GCP, applying CI/CD, logging, monitoring, error handling, and secure deployment best practices
Collaborate with full-stack teams to integrate AI capabilities into end-to-end solutions
Contribute to the ongoing evolution of AOT's AI practice, tooling, and standards
Requirements
Hands-on experience in architecting and developing production-grade agentic AI applications
Experience with any of the code-first agent frameworks and orchestration frameworks such as LangGraph, LangChain, Microsoft Agent Framework, Semantic Kernel, AutoGen, Google - ADK, or similar
Experience with Prompt and Context Engineering principles and strategies
Strong hands-on programming experience in Python or .NET Core or Java
Experience implementing tool calling/function calling with LLMs, which interacts with LOB APIs, databases, enterprise applications, and external tools
Strong understanding of memory and state management in agentic systems
Solid cloud architecture experience on Azure or AWS or GCP
Experience with production engineering practices such as CI/CD (Azure Devops or Github), logging, monitoring, testing, error handling, and secure deployment
Strong understanding of LLM application architecture, including prompts, context management, RAG, vectorization, embeddings, and evaluation
Experience with MCP, A2A, and tool/server integration patterns (Nice-to-Have)
Experience with Azure AI Foundry - Model Deployments, Foundry Projects, Governance (Nice-to-Have)
Previous full-stack development experience (e.g., React/Angular, Python/.NET/Node.js) (Nice-to-Have)
Experience with Docker, Kubernetes, serverless platforms, or cloud-native deployment patterns (Nice-to-Have)
Certifications in AI, ML, or cloud (Nice-to-Have)
Any open-source codebase contributions or references, e.g., Github or GitLab (Nice-to-Have)
Experience in the public sector, financial services, or healthcare (Nice-to-Have)
Any experience with data engineering using Databricks, Microsoft Fabric or Snowflake (Nice-to-Have)
Benefits
Flexible remote work environment with optional hybrid collaboration in Victoria, BC
Continuous learning and leadership development opportunities
Flexible schedules and generous paid time off
Competitive health, dental, and wellness benefits from Day 1
Employer-sponsored deferred profit-sharing plan
A collaborative, mission-driven culture where your work matters
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