Sr. Technical Solutions Architect, AI/Data

Role impact

Solutioning and architecture

• Architect sovereign and on-premise AI solutions using platforms such as NVIDIA AI Enterprise, Dell AI Factory, HPE Private Cloud AI, Red Hat OpenShift AI, Run:ai, and open-source model serving.
• Design generative AI solutions including RAG, CAG, GraphRAG, fine-tuning, and model distillation, as well as agentic systems and MCP-based integrations.
• Design hybrid architectures spanning AWS, Microsoft Azure, and Google Cloud AI stacks.
• Develop reusable reference architectures, decision frameworks, and trade-off analyses for cost, latency, accuracy, governance, and sovereignty.

Client engagement and enablement

• Serve as the senior technical voice in client conversations, from executive briefings to deep technical design sessions.
• Partner with sales, delivery, and practice leadership to scope statements of work, estimate effort, and de-risk delivery.
• Mentor architects, engineers, and consultants through code reviews, internal enablement, and reusable assets.
• Evaluate emerging models, frameworks, protocols, and sovereign AI stacks and bring recommendations to the practice.

Experience and technical qualifications

• 8+ years of progressive experience in software engineering, solutions or enterprise architecture, or applied AI/ML, including at least 2+ years in a hands-on generative or agentic AI role.
• Professional written and spoken fluency in French and English is required for client workshops, executive presentations, and technical documentation.
• Experience with sovereign and on-premise AI, private model serving, enterprise AI platforms, and on-premise vector or graph stores.
• Strong knowledge of GPU architecture, capacity planning, inference optimization, networking, storage, and Kubernetes-based GPU scheduling.
• Strong understanding of data sovereignty, residency, privacy regulations, and air-gapped or disconnected deployments.
• Deep knowledge of at least one of AWS, Azure, or GCP AI platforms, with working knowledge of the other two.
• Production experience shipping RAG and/or agentic systems; practical knowledge of chunking, embeddings, retrieval evaluation, and orchestration.
• Working knowledge of MCP, agent-tool integration, and the design of MCP servers and clients.
• Strong understanding of CAG and RAG variants and their trade-offs.
• Experience integrating REST/GraphQL APIs, Kafka or EventBridge, OIDC/SAML/OAuth2 identity, and platforms such as Snowflake, Databricks, Fabric, or BigQuery.
• Excellent written and verbal communication, including the ability to move between executive narratives and engineering discussions.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent demonstrable experience; an advanced degree is welcomed but not required.

Location and travel

• The role is remote-friendly, with estimated travel of 0–15% to client sites and internal events.

Compensation

• Estimated base pay is CAD 123,760–154,700 annually, plus 30% target incentives.
• Actual salary may vary based on location, experience, skills, education, and related certification.

Benefits

• Benefits for full-time employees include medical and dental care, employee and family assistance, RRSP/DPSP matching, life and disability insurance, paid time off, and an employee discount program.

Hiring process

• The hiring process may use AI to screen, assess, select, or rank applicants, with a hiring team member reviewing candidates before employment decisions.
• Before employment, the company conducts a criminal record check, verifies education, and checks references.