AI Solutions Engineer - Senior and Principal

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 modern 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.
Experience with Azure AI Foundry, Azure OpenAI, AWS Bedrock, or similar managed AI platforms.
Cloud certifications (Azure, AWS, or Google Cloud).
Experience consulting with enterprise clients or working in professional services environments.

Mindset Traits

You thrive in ambiguity and enjoy bringing structure to complex technical problems.
You balance experimentation with engineering discipline.
You communicate clearly with both technical and non-technical stakeholders.
You take ownership from discovery through production support.
You enjoy mentoring others and raising the technical bar around you.
You're curious, pragmatic, and continuously learning as AI technologies evolve.
You care about delivering measurable business outcomes—not just interesting technology.

Why join RAVL?

Work alongside experienced consultants solving meaningful, enterprise-scale challenges.
Help shape the future of AI delivery within one of Canada's leading technology consulting firms.
Flexible, client-aligned hybrid work model—autonomy with accountability, adapting to client delivery needs.
Variable bonus & RRSP contributions tied to performance and delivery impact.
4 weeks paid time off (plus public holidays).
Paid professional development days and continuous learning opportunities.
Comprehensive health & dental coverage, including mental health support.
Commitment to lifelong learning through mentorship, certifications, and continuous improvement.