AI Architect
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Job Description
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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