Title: Principal AI Solution Architect: GenAI, Agentic AI & Platform

Contract - Long Term

Workplace type: Remote

Working hours: PST The Principal AI Solution Architect owns the end-to-end technical architecture for a portfolio of GenAI, agentic AI, RAG, intelligent document-processing, multimodal and AI-enabled application solutions.

The role connects near-term use-case delivery with a reusable platform direction so that teams do not repeatedly solve identity, integration, evaluation, deployment, monitoring, and governance in different ways. This is a deeply hands-on architecture role. The successful candidate personally researches and evaluates relevant technologies, creates technical spikes and reference implementations, contributes code to shared platform capabilities, reviews implementation across the platform and resolves complex issues through code, configuration, traces and working tests.

Required qualifications

- Substantial experience owning architecture for production GenAI, RAG, agentic AI or intelligent automation systems in complex enterprises.
- Current hands-on proficiency in Python and API-based solution development, with sufficient depth to build, debug and review production-quality GenAI and agentic AI code.
- Demonstrated recent contribution to shared AI platform or application repositories, including reference implementations, code reviews, automated tests or production troubleshooting.
- Ability to validate architecture through Azure and Databricks environments,



deployment configuration, traces, evaluation results and working code, not only design documentation.
- Current, practical knowledge of the evolving Microsoft AI ecosystem and recent Azure and Microsoft Foundry capabilities, supported by recent implementation, technical evaluation or production experience rather than certification alone.
- Experience implementing at least one production or production-relevant GenAI platform pattern and using it to deliver an end-to-end use case.
- Experience reviewing code across multiple contributors and converting architectural findings into specific, implementable changes.
- Demonstrated architecture depth across application, integration, data, cloud, security and operational concerns, not only model selection or infrastructure diagrams.
- Strong practical experience with Azure AI capabilities and Databricks, including the ability to validate decisions through working code or prototypes.
- Strong knowledge of agents, tools, MCP, retrieval systems, APIs, distributed systems, identity, observability, evaluation and production governance.
- Experience defining reusable platforms, reference architectures, technical standards and migration paths from experimentation to production.
- Ability to explain trade-offs clearly to engineering teams, business stakeholders, architecture authorities and risk/control partners.
- Robust written communication, decision documentation and technical leadership skills.

📌 Principal AI Solution Architect (Canada)
🏢 Atlantis IT Group
📍 Canada