AI Solution Architect

The Role

We are hiring an AI Solution Architect to own the technical shape of our client engagements end-to-end - from first conversation through to a working system running on the client's infrastructure. You will be the person clients trust to translate ambiguous business problems into well-scoped, defensible AI architectures, and the person our engineering team trusts to keep architectural decisions coherent across the portfolio.

This is a senior, hands-on role. You will spend roughly half your time client-facing - running discovery, leading workshops, presenting architectures, defending design decisions - and the other half deeply technical: designing reference architectures, prototyping critical components, reviewing implementations, and contributing to our accelerator portfolio. This is not an oversight or advisory role; we expect you to write code when the design depends on it, and to know our stack well enough to be credible with the engineering team.

You will report directly to the Founder & CEO and have significant influence on our technical direction, accelerator roadmap, and how we position our work in the market.

What this role is - and isn't

This is a builder's architect role. You will design systems, defend them in front of CIOs and CTOs, and stay close enough to implementation that the architecture survives contact with reality. If you want a role where the deliverable is a slide deck handed off to someone else, this is not the role.

What You'll Do

Client-facing architecture

• Run technical discovery with enterprise and public-sector clients - turning vague problem statements into well-scoped, sequenced engagements with clear architectural choices and explicit trade-offs.
• Design end-to-end reference architectures for agentic AI systems, RAG pipelines, multi-agent orchestrations, and the security and governance layers around them - sized to the client's data, infrastructure, regulatory, and operational constraints.
• Lead workshops and architecture reviews with client technical leaders - CTOs, CIOs, enterprise architects, security leads - and defend design decisions on their technical merits.
• Own the architecture sections of proposals and SOWs, including effort estimation, risk identification, and the assumptions that pricing depends on.

Hands-on technical leadership

• Prototype the highest-risk parts of new architectures yourself - the components where "will this actually work" is the open question - before committing them into client engagements.
• Lead architecture reviews and code reviews for engineering team output, including code generated by AI agents that requires senior review before it ships.
• Make and document the cross-engagement decisions that keep our portfolio coherent - model selection, vector store choice, agent framework, MCP server patterns, deployment topology, observability standards.
• Contribute directly to the design and evolution of our accelerators: the Agentic Penetration Testing Platform, the RFP Automation Platform, the AI Knowledge Fabric, the Agentic SOC, and the AIAP reference implementation.

Security and governance by design

• Embed security, privacy, and governance into every architecture - threat modeling, data residency, access control, prompt-injection defenses, agent runtime controls, audit logging, and human-in-the-loop checkpoints - not as an afterthought.
• Work side by side with our cybersecurity engineering team on AI Agent Zero Trust, agent identity and authorization, and the AIAP architecture that distinguishes our work from typical AI consultancies.
• Translate Canadian regulatory expectations (OSFI E-23, Quebec Law 25, federal Treasury Board Directive on AI) and client-specific compliance requirements into concrete architectural choices.

Pre-sales and growth

• Partner with the founder on pre-sales conversations, particularly for technically demanding prospects in regulated industries.
• Contribute to public-sector RFP responses - bringing the architectural credibility that public-sector evaluators look for.
• Support the team in building thought leadership: reference architectures, technical write-ups, conference talks, and contributions to open-source where it strengthens our position.

What We're Looking For

Required

• 8+ years of cumulative experience across solution architecture, senior software engineering, or applied AI/ML - with at least 2 years shipping production AI or LLM-powered systems (not just pilots or POCs).
• Demonstrated ownership of end-to-end architectures in enterprise environments - designed it, defended it to executives, watched it go to production, and lived with the consequences.
• Strong working knowledge of modern AI building blocks: LLM APIs (Claude/Anthropic, OpenAI, open-weight models), RAG architectures, vector databases, agent orchestration frameworks (LangGraph, LlamaIndex, custom agent loops), MCP, and tool-use patterns.
• Hands-on coding ability in Python (primary). You don't have to write production code daily, but when you sketch an architecture, you can also build the spike that proves it.
• Cloud architecture fluency across at least one major platform (Azure preferred given our client base, AWS or GCP also valued) - including identity, networking, data services, and security primitives.
• Strong grounding in security: data classification, access control, threat modeling, secure design patterns. You understand why "deploy on client infrastructure" is a feature, not a limitation.
• Outstanding client communication. You can stand in front of a skeptical CIO and explain why your architecture is the right one without retreating into jargon, and you can explain it again to the engineering team in code-level detail.
• Located in Canada and legally authorized to work here without sponsorship.

Strongly Preferred

• Direct experience with agentic AI systems in production - multi-agent orchestrations, tool use, human-in-the-loop workflows, agent identity, agent observability.
• Background spanning both AI/data engineering and traditional enterprise architecture (integration, identity, data platforms) - many candidates have one, fewer have both.
• Experience designing systems for regulated industries - financial services, public sector, healthcare - where security, privacy, and auditability are non-negotiable.
• Familiarity with the Canadian enterprise and public-sector landscape: procurement processes, regulatory regimes, vendor ecosystem dynamics.
• Open-source contributor or maintainer in the AI, agent, or security tooling space.

How We Work - and Who Thrives Here

• We treat AI agents as a development force-multiplier. You will work alongside Claude and other AI tools daily - generating code, scaffolding architectures, accelerating research - while applying senior judgment to what ships. Comfort with this operating model is non-negotiable.
• We default to open-source, minimum third-party dependencies, and client-infrastructure deployment.
• We move fast and ship pragmatically. Architectural perfectionism that delays working software is not the standard we hire for.
• We are early-stage. The role will stretch beyond what's written here - sometimes into pre-sales, sometimes into hiring, sometimes into product strategy. People who want a sharply scoped role inside a mature organization will not be happy here.

What We Offer

• Competitive base salary commensurate with senior-level Canadian market rates.
• Meaningful equity participation in an early-stage company backed by AXL.VC.
• Health and dental benefits.
• Fully remote work, anywhere in Canada - with periodic in-person time in Toronto and at client sites.
• A dedicated learning and development budget, including conferences, certifications, and AI tool subscriptions.
• Direct ownership of the technical direction of a company being built from the ground up - not a slot inside someone else's architecture.
• Work that genuinely matters: helping Canadian and global enterprises and public-sector organizations adopt AI safely, with the security discipline the moment requires.