Senior AI Strategist / Solution Architect

Keyrus Canada • Montreal, QC

7h • Hybrid

About The Position

As Senior AI Strategist / Solution Architect at Keyrus, you will own the end-to-end definition of AI strategy and transformation roadmaps for our clients, from AI maturity assessment and cross-department discovery, through use-case prioritization, value hypotheses and governance recommendations, to a sequenced, fundable AI agenda. You will translate real business workflows into a confident "what first" decision: bringing the technical credibility to judge what is feasible and valuable, the consulting skill to align executives and teams, and the perspective to meet each client where they are on their AI journey, while setting standards, contributing to pre-sales, mentoring others, and helping shape our AI advisory practice.

Requirements

• Degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience)
• 7+ years in AI / data / software (with at least 2 year of experience with AI), including hands-on experience taking generative or agentic AI from idea toward production; consulting or client-facing experience is highly valued.
• Hands-on experience building AI agents and generative-AI systems, multi-agent workflows, RAG pipelines, tool/function calling and guardrails — with an orchestration framework (e.g., LangChain / LangGraph or equivalent).
• Hands-on experience with Anthropic Claude and Microsoft Copilot, using and optimizing both in real workflows (Claude Skills / Projects / MCP; Copilot / Copilot Studio), with a clear point of view on where each is the better tool by use case.
• Hands-on experience with at least one major cloud AI platform, e.g., AWS / Amazon Bedrock (foundation models, agents, guardrails) or Azure OpenAI, and the surrounding stack.
• Solid grasp of RAG (embeddings, chunking, hybrid/semantic search, reranking, evaluation, vector databases) and a clear sense of where it does and does not fit.
• Proven ability to lead discovery and assessment, facilitating executive workshops and interviews, mapping workflows, and capturing opportunities in a structured, comparable way.
• Strong command of AI strategy and prioritization, building value hypotheses / business cases and using value × feasibility scoring to make defensible "what first" decisions.
• Strong Python and software-engineering fundamentals (APIs, services, version control, testing), enough to judge feasibility, effort and architecture credibly.
• Proven ability to evaluate platforms objectively and justify architecture and investment decisions to both technical and business audiences.
• A consulting mindset: curiosity, ownership, structured communication, executive presence, and a collaborative, teamwork-first attitude.

Nice To Haves

• Experience designing AI governance, operating models (CoE / Core + Edge) and responsible-AI frameworks in enterprise settings.
• Familiarity with AI maturity assessment frameworks and benchmarking.
• Relevant certifications (e.g., AWS Certified AI/ML or Solutions Architect; Salesforce Agentforce / Platform credentials a bonus).
• Experience comparing and integrating multiple agent platforms within a single architecture.
• Knowledge of regulatory and privacy frameworks (e.g., GDPR, EU AI Act).
• Exposure to front-end (React) for building demos and copilots.
• Experience mentoring engineers or helping build and scale a practice.

Responsibilities

• Lead structured discovery across departments, facilitate workshops and interviews with executives, managers and the people who do the work to map workflows and surface pains; baseline AI maturity across six dimensions (strategy, architecture & tooling, literacy, competences, organization & processes, security & compliance); benchmark it and translate the gaps into prioritized, practical recommendations.
• Turn a wide field of opportunities into a confident shortlist, score and sequence use cases on value × feasibility × complexity with a transparent, weight-adjustable model, build express value hypotheses (benefit, effort, directional value) that make very different initiatives comparable, and consolidate them into a sequenced, multi-horizon roadmap leadership can fund with confidence.
• Bring technical judgment to what's real, screen technical and data feasibility, design target-state architectures for agentic and generative AI (multi-agent workflows, RAG pipelines, tool/function calling, memory and state, guardrails, human-in-the-loop), and tag each opportunity to the best-fit tool the client already owns (separating "do this with current tools now" from "this needs new capability later" so spend is sequenced and justified.)
• Draft right-sized governance, responsible-AI, operating-model and adoption recommendations that scale control with criticality, and communicate the whole story through clear trade-off analyses and executive readouts that land equally well with engineers and the board.
• Contribute to pre-sales and solutioning, mentor consultants and engineers, define best practices, and keep pace with a fast-moving field (new models, frameworks, MCP, agent protocols, governance regimes) — bringing well-judged ideas back to clients and teams.

Benefits

• Group insurance for you and your family members
• RRSP and DPSP participation plan
• Monthly Wellness Allowance
• Reimbursement of telecommunication costs
• Flexible work from home policy
• 4 weeks of paid vacation
• Language courses (French & English)
• Access to continuing education (in-house, conferences, events, courses, certifications, etc.)
• Development plan for each employee and coaching

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree