Technical Solutions Manager (AI Architect)

Kyndryl • Regina, SK

7d • CA$60,000 - CA$85,000 • Hybrid

About The Position

Kyndryl is seeking a Technical Solutions Manager (AI Architect) to support client engagements by discovering business needs, translating them into AI requirements, and assisting in the design and delivery of AI solutions. This role involves client-facing consulting, including presentations and workshops, as well as hands-on AI exploration like research and prototyping. The architect will design scalable, intelligent architectures incorporating AI services, data pipelines, and cloud-native platforms, guiding cross-functional teams in implementing resilient, secure, and optimized solutions. The position emphasizes continuous modernization, intelligent automation, and the ethical use of AI. This role is ideal for someone comfortable communicating with stakeholders and eager to grow their technical and consulting expertise.

Requirements

• University Degree in a relevant discipline (e.g., Computer Science, Data Science, Engineering, Information Systems, Statistics, or related).
• At least one (1) year of relevant experience in one or more of: AI/ML, analytics, data engineering, or software delivery; consulting, business analysis, or client-facing technology roles; applied research, labs or internship experience with demonstrable outcomes.
• Demonstrated ability to present to clients and explain technical concepts in plain language (slides, demos, or written artifacts).
• Demonstrated ability to facilitate requirements gathering (workshops/interviews) or strong aptitude with examples.
• Foundational knowledge in at least two of the following: ML basics (supervised/unsupervised concepts, evaluation metrics), LLM concepts (prompting, RAG, hallucinations, evaluation), data fundamentals (data quality, schemas, pipelines at a conceptual level), software fundamentals (APIs, version control, testing concepts).
• Demonstrated ability to synthesize ideas and use abstract thought to understand new business domains.
• Demonstrated ability to lead and positively influence others to achieve results that meet the organization’s strategic objectives.
• Basic level project management skills would be considered an asset.
• Demonstrated administration and organizational skills.
• Excellent oral and written communication skills.

Nice To Haves

• Exposure to cloud AI services or platforms (e.g., Azure/AWS/GCP concepts).
• Familiarity with responsible AI concepts (privacy, bias, explainability) and practical mitigations.
• Experience coordinating small teams (student projects, labs, internships, volunteer leadership).
• Basic project delivery methods (Agile/Scrum exposure).
• Strong facilitation skills: ability to guide conversations, ask structured questions, and synthesize outcomes.
• Analytical mindset with structured problem solving and comfort working with ambiguity.
• Proven ability to synthesize ideas and interpret abstract concepts.
• Ability to manage multiple priorities and meet deadlines.
• Curiosity and learning agility; proactive research and experimentation habits.
• Team-oriented; able to collaborate across technical and non-technical audiences.
• Professionalism with clients: responsiveness, clarity, and follow-through.

Responsibilities

• Participate in and facilitate requirements gathering activities such as discovery sessions, interviews, and workshops.
• Document and validate requirements, including problem statements, success measures, constraints, assumptions, and risks.
• Architect and design enterprise application solutions.
• Assess current systems management practices.
• Perform service level agreement negotiation and documentation.
• Prepare and deliver client-ready presentations (findings, options, recommendations, prototypes, and progress updates).
• Translate business needs into AI use cases, including value hypotheses, feasibility considerations, and ethical/risk considerations.
• Support stakeholder alignment by summarizing trade-offs (e.g., accuracy vs. explainability; cost vs. performance; build vs. buy).
• Contribute to project artifacts such as meeting notes, decision logs, RAID logs, and statements of work content (as directed).
• Assist with solution design activities including: data understanding and readiness assessment (high level), feature / signal brainstorming, evaluation approach definition (metrics, baselines, acceptance criteria), model/service integration considerations (APIs, workflows, monitoring needs).
• Support the creation of prototypes / proofs of concept using approved tools and patterns (e.g., prompt prototypes, small ML experiments, retrieval approaches).
• Help define and execute experiments: test plans, evaluation datasets (where provided/approved), and results summaries.
• Contribute to technical documentation (solution overview, model cards/AI notes, evaluation summaries, runbooks) at an appropriate level for the audience.
• Follow organizational standards for security, privacy, and responsible AI practices as defined by project governance.
• Research emerging AI capabilities and patterns relevant to client problems (e.g., agentic workflows, RAG approaches, evaluation techniques).
• Run structured experiments to compare approaches and document what worked, what didn’t, and why.
• Contribute reusable assets such as templates, checklists, demo scripts, prompt libraries, and “lessons learned” write-ups.
• Lead a small pod/workstream of AI specialists (e.g., 1–3 people) on well-scoped tasks by: clarifying goals and deliverables, coordinating work and dependencies, facilitating short stand-ups/check-ins, ensuring quality and timely completion.
• Collaborate effectively in a matrixed environment with engineers, analysts, product owners, and client stakeholders.
• Seek mentorship and provide peer support through knowledge-sharing and constructive feedback.
• Support delivery management by maintaining task status, raising risks early, and helping keep work aligned to timelines.
• Contribute to estimates for small tasks (effort ranges, assumptions) and track progress against commitments.
• Assist with proposal/support materials (e.g., case study summaries, demo packaging) when needed.

Benefits

• Flexible, supportive environment where your well-being is prioritized and your potential can thrive.
• Be Well programs designed to support financial, mental, physical, and social health.
• Impactful work that powers the systems our customers rely on.
• Opportunities to sharpen skills and fuel growth through meaningful projects.
• Tools to chart career path, personalized development goals, and continuous feedback.
• Access to cutting-edge learning opportunities—from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level