Principal AI Architect

Trend Micro•Ottawa, ON

About The Position

TrendAI™, the global AI security leader and enterprise business unit of Trend Micro, empowers organizations with full AI visibility and consolidated security that inspires confidence, drives innovation, and eliminates risk. At TrendAI™, we’re always seeking exceptional talent; people who want to collaborate with the best and push boundaries together. Here, your work goes beyond building a career. You will help protect what matters and play a vital role in shaping a safer, more trustworthy AI-powered future. AI Fearlessly. About the Role TrendAI’s security products protect hundreds of millions of devices and cloud workloads worldwide. As AI reshapes how security systems are built and operated, we are investing in the architects who can design AI-native systems from first principles — not just integrate AI into existing stacks, but rethink what those stacks should look like. We are looking for a Principal AI Architect with deep technical roots in a security domain, genuine fluency in agentic AI systems, and — as that credibility builds over time — the ability to represent TrendAI’s technical thinking at the world’s most demanding venues. This is a senior individual contributor role with real ownership. You drive the technical direction of strategic AI initiatives — from shaping product architecture early in the design cycle, through hands-on technical validation, to ensuring the solution lands the way it was intended. You earn your influence not through seniority alone, but through the quality of your judgment and your ability to move things from idea to working reality.

Requirements

Deep Technical Foundation in a Security Domain
Hands-on background in security engineering or research — AI security, threat detection, cloud security, vulnerability research, or large-scale telemetry systems
Deep understanding of at least one security domain at production scale: the internals, the failure modes, the constraints that textbooks skip
A track record — shipped systems, published research, CVEs, open-source contributions, or conference presentations that demonstrate real depth
Genuine Enthusiasm for New Technology
Intrinsically motivated to understand emerging AI capabilities and translate them into practical security applications — not just following trends, but forming independent views
Comfortable operating at the frontier: reasoning carefully about what is real, what is hype, and what is genuinely novel
Proactively explores adjacent domains — offensive security, ML research, systems architecture — and synthesizes insights across them
Agentic AI Fluency
Production experience with LLM/SLM integration, agentic workflow design, or multi-model systems
Can reason about the full agentic stack: planning, tool use, memory, orchestration, and the human oversight layer
Understands inference trade-offs — latency, privacy, accuracy, evasion resistance — and how they interact with security system requirements
Familiar with the failure modes specific to agentic systems in adversarial environments
Independent Judgment
Pushes back when architecture doesn’t hold up — not swayed by schedule pressure, demo quality, or seniority in the room
Represents engineering truth, not the convenient answer
Builds credibility through the quality of analysis, not through authority

Nice To Haves

Experience with adversarial ML, AI red-teaming, or AI system threat modeling
Familiarity with AI security product development — AI supply chain risk, model integrity, prompt injection defense, or agentic system guardrails
Prior work at or collaboration with TrendLabs, ZDI, or equivalent threat research organizations
Published CVEs, conference papers, or open-source security tooling
Background spanning both offensive security and AI/ML systems
Experience with large-scale security telemetry, XDR correlation, or cloud-native security architectures
Has spoken at, published in, or contributed to recognized security or AI venues
Recognized — or on a clear trajectory to be recognized — as a technical voice in the field

Responsibilities

Own the architectural vision for how AI integrates into your domain — from on-device inference and cloud-assisted pipelines to fully agentic decision workflows
Design AI-native systems from the ground up, not as layers on top of existing architectures
Define trade-off frameworks for AI capabilities within real production constraints: latency, resource budgets, accuracy, evasion resistance, and platform-specific requirements
Assess AI feature proposals for architectural soundness, data dependency risks, and long-term maintainability
Identify where consolidation or modernization efforts create AI architecture opportunities — and where they introduce compounding risk
Design the boundary between autonomous AI decision-making and human expert judgment in critical security workflows
Architect multi-agent systems and agentic pipelines appropriate for high-stakes security environments: tool use, orchestration, memory, and guardrails
Reason rigorously about failure modes in agentic systems — hallucination under adversarial input, over-automation, cascading errors, and loss of human oversight
Stay at the frontier of agentic AI research and translate emerging capabilities into concrete architecture proposals
Drive the technical direction of key AI product initiatives from early concept through architecture validation and implementation — not just advising, but owning the technical narrative end to end
Lead the technical case-making for strategic initiatives: structure the problem, define evaluation criteria, pressure-test design options, and build the artifacts that move decisions forward
Work hands-on to validate technical approaches — prototype where needed, review implementation against architecture intent, and course-correct when execution drifts from design
Collaborate with product, engineering, and research leads to translate strategic bets into technically grounded roadmaps with clear dependencies and risk profiles
Hold the technical bar on critical initiatives: push back on shortcuts, identify when a direction is fundamentally unsound, and propose alternatives that are both rigorous and achievable
Define what meaningful AI adoption looks like for engineering and research teams — beyond tool usage, into workflow integration and architectural thinking
Identify engineers and teams who are genuinely advancing AI-native development and help systematize what they are doing
Build evaluation frameworks that engineering leadership can act on
Advise on AI tooling that genuinely accelerates work, and flag where AI introduces risk rather than leverage
Opportunities to represent TrendAI R&D at security and AI venues relevant to your domain: Black Hat, DEF CON, RSA, GTC, AWS re:Inforce, and academic forums
Present at TrendAI’s own global platforms — including the TrendAI Spark global series and invite-only Spark Leadership Exchange — in front of enterprise security leaders and C-suite audiences
Engage with enterprise customers in Executive Briefing Center (EBC) settings as relevant experience builds, translating complex AI architecture decisions into clear, business-relevant narratives for senior decision-makers
Contribute to external discourse through technical blog posts, conference presentations, and original research, as interest and opportunity align
Engage with MITRE ATLAS, OWASP, and relevant standards bodies to help shape how AI security practices are defined industry-wide
Operate as a technical peer to CTO- and CISO-level counterparts at strategic partners and enterprise customers