Solutions Engineer at Qohash managing technical resources and driving new business in Quebec and European territories. Lead customer engagements and support complex enterprise sales with a focus on data security.
About the role
- AI Solution Architect shaping AI use cases from idea to delivery at major financial services client. Defining solution architectures and driving platform consolidation with Microsoft Foundry expertise.
Responsibilities
- Define end-to-end solution architectures for AI use cases across a financial services enterprise, from use case shaping through solution-on-a-page delivery.
- Provide L1 estimates and right-size technical approaches to client constraints, timelines, and platform capabilities.
- Drive platform consolidation by identifying reuse opportunities across lines of business and rationalizing overlapping tooling.
- Design and document integration patterns using Microsoft Foundry and its component services - Document Intelligence, Content Understanding, Azure OpenAI Service, and Foundry Models.
- Navigate enterprise governance including responsible AI forums, cloud onboarding processes, and security/compliance review gates.
- Translate business requirements into decomposed, estimatable backlogs that engineering teams can build against.
- Embed with client solution architects and delivery teams, operating as a trusted technical authority from day one.
- Produce technical artifacts - architecture diagrams, integration maps, decision records - that drive alignment across business and technology stakeholders.
- Identify and escalate architectural risks early, proposing mitigations before they become delivery blockers.
- At higher levels: shape AI strategy across the portfolio, influence platform direction, and mentor junior architects and engineers.
Requirements
- Strong architecture skills across Microsoft Foundry and its Foundry Tools - Document Intelligence, Content Understanding, Azure OpenAI Service, Foundry Models, Foundry IQ.
- Hands-on experience designing AI/ML solution architectures in enterprise environments, ideally financial services.
- Deep understanding of document processing pipelines, including OCR, classification, extraction, and enrichment patterns.
- Experience with LLM integration patterns - prompt engineering, RAG architectures, fine-tuning workflows, and guardrails.
- Proficiency with Python for prototyping, proof-of-concept development, and pipeline scripting.
- Solid grasp of API design, microservices, and event-driven architectures in cloud-native environments.
- Experience working within enterprise governance frameworks - responsible AI, model risk management, cloud onboarding, security review.
- Strong understanding of data integration patterns across multiple lines of business and legacy systems.
- Familiarity with DevOps/MLOps tooling - CI/CD pipelines, infrastructure as code, model deployment and monitoring.
- Knowledge of identity, encryption, RBAC, and secrets management in regulated cloud environments.
- Experience producing architecture decision records, solution-on-a-page documents, and integration diagrams for senior stakeholders.
- Comfortable working cross-functionally with engineering, business analysis, and executive sponsors.
- Clear written communication skills for technical documentation, governance submissions, and stakeholder briefings.
Benefits
- Flexible, client-aligned 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 — continuous improvement through training, mentorship, and certification
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