AI Solutions Architect (Senior and Principal)

What does success look like in this role?

• 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.

• 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.