Staff Engineer or Architect (Agentic AI Team) at Trulioo

Position Summary:

Reporting to the Director of Software Engineering, the Staff Engineer or Architect (Agentic AI Team) will be responsible for designing, building, and owning agent systems end-to-end—from design through production. This role involves building reliable, steerable, multi-step agent workflows that plan, execute, observe outcomes, and iteratively improve.

This role is expected to leverage AI and emerging technologies to improve productivity, enhance decision-making, and continuously optimize how work is performed.

This will be a full-time, permanent position, either working out of the Vancouver office on a hybrid model (3-days per week in the office) or remotely within North America.

What You’ll Be Doing:

• Design, build, and own agent systems end-to-end—from design through production—for identity, fraud, risk, and commerce workflows. You own the eval harness and observability for what you ship, not just the happy path.
• Build reliable, steerable, multi-step agent workflows that plan, execute, observe outcomes, and iteratively improve—including tool use and human-in-the-loop patterns appropriate to regulated, high-stakes decisions.
• Troubleshoot novel, non-deterministic failures across models, tools, orchestration, and infrastructure. Stay calm under ambiguity, form hypotheses, instrument the system, and find the root cause.
• Work in a compliance-heavy, globally regulated domain where auditability, correctness, and human oversight are features, not afterthoughts.
• Set and communicate a technical vision to teammates and agents you direct. Make the implicit explicit: a spec an agent can execute is a spec a teammate can trust.
• Leverage AI and emerging technologies to improve productivity, streamline workflows, and identify opportunities for continuous improvement while ensuring the responsible, secure, and compliant use of AI tools.
• Orchestrate AI agents in your daily work and hold the bar on what they produce. Keep a clear mental model of the system, verify what changed, and stay accountable—AI is a force multiplier, not an excuse.

What You’ll Bring:

• 8+ years of software engineering experience with demonstrated impact on production systems.
• Fluency using AI agents in your own engineering workflow—you can show us how you keep a mental model, verify outputs, and stay accountable while moving faster with AI.
• Demonstrated ability to own features end-to-end and communicate trade-offs clearly to both technical and non-technical stakeholders.
• Experience working on challenging, novel, or ambiguous projects where you had to define the problem, not just solve a handed-down spec.
• Hands-on experience building with LLMs—prompt engineering, RAG, tool use, and at least one agent framework (e.g. LangGraph, CrewAI, AutoGen, or similar), plus evaluation frameworks for agent behavior.

Nice to Have:

• Experience in financial services, identity, fraud, or risk domains, or other compliance-heavy environments (e.g., AML, fraud rules engines, identity graphs, risk scoring).
• Multi-agent orchestration patterns and production-grade evaluation harnesses.
• AI observability tooling; MLOps practices (experiment tracking, model registries, feature stores).
• Vector databases, knowledge graphs, or structured retrieval for agent memory.