We design, build, manage and modernize the mission-critical technology systems that the world depends on every day.
Technical Solutions Manager – AI Architect
Location
Canada
Posted
2 days ago
Salary
$60K - $85K / year
Seniority
Junior
Job Description
Technical Solutions Manager – AI Architect
Kyndryl
• 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.
Job 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.
Benefits
- Flexible work arrangements
- Professional development opportunities
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