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AI Solutions Architect; Senior and Principal

Job in Toronto, Ontario, C6A, Canada
Listing for: RAVL
Full Time position
Listed on 2026-09-23
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, Cloud Engineer - Software, Backend Developer
Salary/Wage Range or Industry Benchmark: 120000 - 170000 CAD Yearly CAD 120000.00 170000.00 YEAR
Job Description & How to Apply Below
Position: AI Solutions Architect (Senior and Principal)

RAVL helps technologists accelerate their careers.

At RAVL, we connect strategy with execution, care deeply about the people we work with, and measure success by the lasting impact we leave behind. Our purpose is to build a team that puts real, sustainable business outcomes at the core of everything we do.

We're here to leave our clients better than we found them—and to create a place where our people are proud to Build. Better.

About

The Role

We're looking for an experienced AI Solutions Engineer to help our financial services clients turn ambitious AI ideas into secure, scalable, production-ready solutions.

This is a software engineering role with an AI specialization
, not a prompt engineering role. You'll design and deliver AI-enabled applications and agentic systems that integrate with enterprise platforms, business workflows, and governance requirements. You'll work alongside client teams to navigate ambiguity, make pragmatic architectural decisions, and deliver measurable business outcomes.

As a Senior or Principal engineer, you'll bring technical leadership to complex engagements, influence solution direction, mentor teammates, and help shape RAVL's growing AI engineering practice.

What does success look like in this role?
  • Own the GCP side of the target architecture as a first-class cloud: landing zone, resource hierarchy, Shared VPC, and Organization Policy on Google Cloud
  • Set the GCP reference patterns other pods build on:
    Cloud IAM and Workload Identity, VPC Service Controls, Cloud KMS, and Artifact Registry
  • Design, build, and deliver production-ready AI-enabled applications and intelligent agents with robust testing, observability, and operational resilience
  • Architect solutions that deliberately balance agents, workflows, retrieval, tools, memory, and human oversight—and recognize when traditional software is the better solution
  • Integrate foundation models with enterprise systems including APIs, identity platforms, business applications, and data sources using secure, well-defined contracts
  • Develop evaluation frameworks that measure AI quality using automated testing, regression suites, trace analysis, and business outcome metrics—not just successful demonstrations
  • Design AI systems that meet financial-services expectations around privacy, auditability, security, governance, authorization, and responsible AI
  • Partner closely with clients to understand business challenges, translate ambiguity into actionable delivery plans, and communicate technical decisions with clarity
  • Lead technical discussions, mentor engineers, conduct architecture reviews, and contribute reusable patterns that strengthen both client delivery and RAVL's AI capabilities
  • Continuously improve engineering practices by identifying opportunities for automation, standardization, and operational excellence across engagements
Sounds great, but do my skills fit?

We're looking for engineers who combine strong software engineering fundamentals with practical experience building AI-powered systems.

  • Hands-on GCP architecture, not Azure or AWS only: landing zones, resource hierarchy, Shared VPC, and Org Policy
  • Deliberate GCP-versus-Azure trade-offs and portable patterns across both clouds
  • Professional software engineering experience using Python or Type Script, with a strong focus on clean architecture, testing, maintainability, and production quality
  • Experience designing distributed systems and integrating enterprise APIs, including authentication, authorization, resilience, idempotency, and service boundaries
  • Hands-on experience building AI-enabled applications using modern LLM frameworks, orchestration patterns, retrieval-augmented generation (RAG), tool use, memory strategies, and human-in-the-loop workflows
  • Experience evaluating AI…
Position Requirements
10+ Years work experience
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