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. You 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 to the agents you direct. You 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. You 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 (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.
Interview Process:At Trulioo, we strive to create an interview experience that is transparent, engaging, and respectful of your time. Our process is designed to help us learn more about your skills and experience while giving you insight into our team, culture, and the impact of the work we do.
Here's what you can expect throughout the interview process:
- Recruiter Interview: 30 Minutes
- Hiring Manager Interview: 30 Minutes
- Technical Interview: 120 Minutes
- Final Leadership Interview: 30 Minutes
