Ai Solutions Architect (Senior And Principal)
$120k - $170k per yearRAVL
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 RoleWe'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 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 stakeholdersYou 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
Compensation & Hiring ProcessThis is a
current permanent opportunity .
The salary range for this role is
$120,000-$170,000 CAD, reflecting expected base pay. Total compensation may also include additional pay such as bonuses or incentives, depending on the position, and final offers are based on experience, skills, and qualifications.
As part of our hiring process, we may use technology, including AI-based tools, to help summarize and assess applications. These tools assist our team and do not replace human review or decision-making.
Equal Opportunity & AccessibilityRAVL is an equal opportunity employer committed to building a diverse, inclusive, and accessible workplace. We welcome applications from all qualified individuals and provide accommodations throughout the hiring process upon request.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
#J-18808-Ljbffr
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 RoleWe'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 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 stakeholdersYou 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
Compensation & Hiring ProcessThis is a
current permanent opportunity .
The salary range for this role is
$120,000-$170,000 CAD, reflecting expected base pay. Total compensation may also include additional pay such as bonuses or incentives, depending on the position, and final offers are based on experience, skills, and qualifications.
As part of our hiring process, we may use technology, including AI-based tools, to help summarize and assess applications. These tools assist our team and do not replace human review or decision-making.
Equal Opportunity & AccessibilityRAVL is an equal opportunity employer committed to building a diverse, inclusive, and accessible workplace. We welcome applications from all qualified individuals and provide accommodations throughout the hiring process upon request.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
#J-18808-Ljbffr
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