AI Engineering Lead

The bet

This is the most senior engineering hire Bold AI will make, this week. The person in this role owns the technical spine of the company: the agent platform our clients run on, the methodology our engagements deploy, and the engineering pattern that makes the next ten transformations cheaper than the first.

We are an applied AI company in active scale. Our clients are real. Our deployments are in production. The gap between where we are now and where the work is going needs an engineer who has built enterprise agentic systems before, knows how to architect for the next two years rather than the last six months, and is ready to own that function end to end.

If that's the role you've been looking for, keep reading.

About Bold AI

Bold AI is the partner enterprises hire when they want AI to mean something at the organizational level rather than the individual desk. We deliver structured transformation engagements grounded in our PIE methodology and the four-mode AI arc (Assistants, Co-Pilots, Agents, Autopilots), built on Microsoft Azure and Copilot Studio, and shipped through Microsoft Teams into the daily flow of work and beyond.

Our clients span Canadian financial services, commercial real estate lending, consumer electronics giants, large-scale produce growers, sporting goods and apparel, retirement community operators, and enterprise events. We deploy across regulated industries where compliance and IP ownership are not afterthoughts. Every deployed agent is owned outright by the client. Every methodology and engineering pattern is owned outright by Bold AI.

We are a small, fast-moving team. The technical decisions made in this role will shape the platform for the next several years.

What you'll own

Architecture and vendor strategy

• Own end-to-end technical architecture across Bold AI's products and client engagements.

• Define and defend vendor, model, and platform decisions with full consideration of cost, scalability, dependency risk, and regulatory exposure.

• Select and implement the right orchestration layers, agent harnesses, and control plane tooling for each engagement.

• Evolve infrastructure strategy as client load and product complexity scale.

• Identify and address technical debt before it constrains the business.

Enterprise agentic systems

• Design and ship production-grade agentic workflows: multi-step, multi-agent, with robust state management, failure handling, and human-in-the-loop checkpoints.

• Evaluate and integrate orchestration frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, Microsoft Agent Framework, or equivalents) on engagement-by-engagement merit.

• Build control planes that give enterprise clients visibility, auditability, and governance over AI behaviour.

• Own prompt architecture, model selection, token economics, and output reliability at scale.

• Stay current on the enterprise agentic stack and assess new tooling critically before adoption.

Compliance, security, and enterprise readiness

This is a leadership function, not a checklist. The compliance pattern you set is the pattern every future Bold AI engagement inherits. It is also the function that gates every enterprise sale.

• Define and own Bold AI's compliance posture: data handling, residency, encryption, access control, audit trail, and incident response.

• Architect for enterprise-grade compliance across Bold AI's own platform and every client deployment, including SOC 2, ISO 27001, and sector-specific obligations in financial services and other regulated industries.

• Be the technical interlocutor for client InfoSec, legal, and procurement teams during enterprise due diligence.

• Set the IP boundary architecture that gives clients full ownership of their deployed agents and data while protecting Bold AI's methodology, frameworks, and reusable engineering patterns.

Team and client leadership

• Demonstrated strategic front room leadership with confidence. You will be in client rooms with CFOs, COOs, CIOs, and InfoSec leaders. You will translate architecture into business decisions for non-engineers and represent Bold AI as the senior technical voice in steering committees, sales conversations, and post-mortem reviews. This is half the job.

• Lead, mentor, and set the technical standard for a team of engineers and an automation lead.

• Own code review culture, deployment practices, and engineering quality across the team.

• Partner with the Product Lead to translate strategy into a scoped, sequenced roadmap.

What success looks like in six months

Multiple deployed agent harnesses in production at named enterprise clients. A reusable engineering pattern that any new engagement can extend. A control plane that gives every client visibility, auditability, and governance over their AI behaviour. A documented compliance posture that survives enterprise InfoSec review. A small engineering team shipping to your standard. Architectural decisions documented well enough that the next engineer ramps in two weeks rather than three months.

If those outcomes feel like a stretch, this is not the role. If they feel like the floor, keep going.

What we're looking for

• 10+ years in engineering, with 3+ years building and operating AI and LLM systems in production.

• Hands-on experience designing and shipping enterprise agentic solutions in regulated or enterprise environments, not lab settings.

• Deep technical judgment on LLM selection, orchestration trade-offs, harness patterns, control plane design, and infrastructure decisions.

• Demonstrated strategic front room leadership with confidence. Comfortable and credible as the senior technical voice in enterprise client conversations across executive, InfoSec, legal, and procurement audiences.

• Track record leading and growing a small engineering team while remaining a strong individual contributor.

• Experience setting and operating an enterprise-grade compliance and security posture across infrastructure and client deployments.

Preferred

• Multi-tenant AI platform experience for enterprise clients.

• Direct experience leading SOC 2 or ISO 27001 readiness.

• Background in AEO, GEO, or AI-answer search optimization.

• Experience with analytics platforms or spatial data systems at scale.

• Prior experience as the first or most senior technical hire at an early-stage company.

The stack you'll work in

• Model layer: Anthropic Claude, OpenAI and Azure OpenAI, with Claude as the default for high-quality work. Most Bold AI client deployments run on this stack.

• Microsoft ecosystem (primary deployment substrate): Azure AI Services, Copilot Studio, Power Platform, Microsoft Teams, SharePoint, Active Directory.

• Agent frameworks: LangGraph, AutoGen, CrewAI, Semantic Kernel, Microsoft Agent Framework, or equivalents on engagement-by-engagement merit.

• Control plane and observability: LangSmith, Arize, Weights and Biases, or comparable.

• Infrastructure: Azure as primary, plus GCP, Railway, Supabase, or similar cloud-native stacks where engagements require.

• Patterns: Vector stores, RAG pipelines, and retrieval architecture at production scale. API design, async systems, and event-driven architectures.

Location, compensation, and structure

Toronto-based or remote across Canada. Compensation includes upside. We will discuss range and structure once we have established mutual fit.

How to apply

Send a short note on the most significant agentic system (that’s live today) that you have shipped to production, what you would change about it if you were starting over, and the architectural decision you are most proud of. We read every one.