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 TypeScript, 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 contemporary LLM frameworks, orchestration patterns, retrieval-augmented generation (RAG), tool use, memory strategies, and human-in-the-loop workflows

Experience evaluating AI systems through structured testing, trace analysis, regression testing, and measurable quality metrics

Strong understanding of secure software development and responsible AI practices, particularly around privacy, governance, prompt injection, auditability, and access controls

Experience collaborating directly with stakeholders to translate business problems into practical technical solutions

For Senior and Principal candidates, demonstrated experience leading technical initiatives, influencing architecture decisions, mentoring engineers, and navigating ambiguity on complex delivery engagements

Extensive experience in GCP environments

Nice To Have Skills

Experience delivering AI solutions within banking, insurance, wealth management, or capital markets

Experience designing intuitive human-AI experiences that improve user adoption and trust

Experience with multimodal AI or model adaptation techniques

📌 AI Solutions Architect (Toronto)
🏢 RAVL
📍 Toronto