Artificial Intelligence

• Design and implement AI-driven solutions, including LLM-based applications, agentic workflows, and automation systems
• Build multi-step data pipelines for document processing, transformation, validation, and error handling
• Develop semantic search and RAG-based solutions using embeddings, vector databases, and retrieval pipelines
• Engage with business stakeholders to understand complex workflows and identify opportunities for AI adoption
• Translate business requirements into scalable technical architectures and solution designs
• Ensure integration with enterprise platforms, data sources, and governance systems

Senior Associate – AI Consulting, Insurance

• Work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment
• Own the end-to-end implementation of Pigment’s AI capabilities for strategic customers
• Manage the translation of business problems into models
• Collaborate closely with Customer Success, Solutions Architects, and Product teams
• Train users and teams on Pigment features, modeling best practices, and scalable system design

AI Deployment Strategist

• Analyze business needs that can be supported by artificial intelligence.
• Recommend relevant, secure, and responsible AI approaches.
• Design or contribute to proofs of concept.
• Support the integration of AI services into existing applications.
• Analyze data, security, governance, and privacy issues.
• Recommend control, validation, and monitoring mechanisms.
• Document technological choices, limitations, risks, and recommendations.
• Collaborate with architects, analysts, developers, and security experts.

Artificial Intelligence Expert

• Getting hands-on education in AI automation with real projects.
• Working on automation projects that save time and improve workflows.
• Designing and deploying practical AI agents that solve real problems.
• Collaborating across the business to uncover repetitive workflows and bottlenecks.
• Bridging operational teams and technical implementation for AI solutions.
• Maintaining a transformation dashboard tracking AI impact on efficiency.
• Navigating AI governance, data risk, and responsible AI implementation.

AI Automation Intern

• Develop and execute a comprehensive AI platform roadmap aligned with Zayo’s business objectives
• Lead the research, evaluation, and implementation of large-scale AI models, including LLMs, transformer-based models, computer vision, and multimodal AI
• Design and deploy AI solutions for predictive analytics, intelligent automation, operational optimization, and real-time decision-making
• Oversee the end-to-end AI lifecycle, including data engineering, model development, testing, deployment, monitoring, and continuous improvement
• Build and optimize scalable AI infrastructure using cloud platforms such as AWS, Azure, or Google Cloud, along with GPU and TPU-based distributed training environments
• Implement modern MLOps frameworks to support efficient model deployment, governance, observability, reliability, and performance monitoring
• Build, mentor, and lead a high-performing team of AI researchers, machine learning engineers, data engineers, and AI platform specialists
• Partner with engineering, network operations, product, data, security, compliance, and business teams to identify high-value AI use cases and ensure business alignment
• Establish responsible AI practices that address bias, fairness, transparency, model risk, security, and regulatory compliance
• Drive measurable business outcomes through AI-enabled improvements in efficiency, service reliability, customer experience, and operational decision-making.

Head of AI – Platforms

• Lead teams responsible for the design, development and deployment of artificial intelligence solutions (machine learning, generative AI and agentic AI)
• Oversee budget management, unit performance, and embody the organizational culture
• Be accountable for the end-to-end delivery of AI solutions
• Drive the lifecycle management of AI solutions
• Ensure the quality, compliance and performance of delivered AI solutions
• Manage and grow the AI center of expertise

Senior Director – AI Solutions

• Strategy — Refine the ICP, pricing model, and product positioning
• Customer Development — Lead pilots with VPs, operations managers, and merchandise planners at importers, distributors, and multi-channel retail brands, convert them to paid engagements, and build the go-to-market motion
• Product — Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback
• Capital — Lead the seed raise, supported by FutureSight's network and traction
• Team — Recruit and lead the founding team, and establish the cultural foundation of the company

Co-Founder & CEO – AI Retail Planning

• Administer Intact’s AI Governance Framework: Lead the maintenance and continued development of an enterprise-wide AI governance framework, policies, and procedures.
• Lead GenAI enablement and adoption across business units, including the adoption playbook, as well as support for selecting the right GenAI tools to maximize business value while managing risk.
• Ensure Regulatory Compliance: Stay ahead of the rapidly evolving global AI regulatory landscape, including the EU AI Act, and ensure that all of Intact's AI systems and practices are compliant with applicable laws and regulations.
• Risk Management: Identify, assess, and mitigate AI-related risks, including algorithmic bias, data privacy, model inaccuracies, and security vulnerabilities.
• Champion our AI strategy story: Oversee the Strategy team responsible for coordinating and creating strategic presentations that effectively convey the company's AI, data, and digital strategies, vision, and value proposition.
• Ethical Oversight and Responsible AI: Champion the ethical and responsible use of AI across the organization.
• Stakeholder Collaboration: Work closely with cross-functional teams, including data science, legal, compliance, information security, and business units, to align AI governance with broader organizational objectives.
• Governance and Reporting: Prepare the AI governance steering committee and specialized working groups. You will prepare and present regular reports on AI governance activities, risks, value generation and compliance to senior leadership.

Director, AI Strategy – Governance

• Own and manage the delivery roadmap for the augmentation portfolio across business units, ensuring clear timelines, milestones, and value realization
• Lead solution delivery across both low-code rapid deployments and complex builds, ensuring high standards of accuracy, reliability, and adoption
• Serve as the primary business partner to central Technology teams, aligning augmentation solutions with foundational technology investments
• Oversee operational quality, governance, and release readiness, ensuring all capabilities meet defined acceptance criteria and audit standards
• Build and develop high-performing teams, while engaging stakeholders and communicating outcomes to business leaders and executives
• Drive capacity planning, prioritization, and continuous improvement of the shared augmentation library to maximize long-term value

Director, Intelligent Automation – AI

• Manage end-to-end deployment of software implementations, upgrades, and security fixes across hybrid environments
• Spearhead the adoption of intelligent automation technologies to optimize delivery processes
• Orchestrate end-to-end SCCM package deployment to desktop, laptop, virtual machine, and cloud environments using intelligent workflows
• Gather and interpret customer requirements using data-driven insights to identify optimal solutions
• Conduct data analysis and generate AI-powered predictive reports for customers and partners

Software Delivery Analyst – AI-Enabled Transformation

• Lead end-to-end delivery of Data & AI programs across planning, execution, and governance
• Build relationships with executives and key stakeholders to align on outcomes
• Translate technical solutions into business value and strategy
• Drive program governance including scope, risks, and dependencies
• Oversee Microsoft Fabric implementations and data platform modernization
• Coordinate cross-functional teams (engineering, analytics, AI)
• Facilitate executive steering committees and decision forums
• Develop adoption and change management strategies
• Monitor delivery performance using KPIs, dashboards, and reporting
• Support business development and client engagement activities

Data & AI Manager

• Develop level 1 AI skills and some level 2 skills based on specifications generated during workshops
• Deliver approximately 8 to 12 deployment-ready AI skills per month
• Perform testing and validation of AI skills prior to final review and deployment
• Maintain skills documentation and update the internal AI skills registry
• Support user training sessions and collect feedback from teams
• Build test-case libraries and QA processes for the different departments
• Continuously improve outcomes through iteration and prompt refinement

AI Skill Builder

• Embed directly with clients to run discovery, interviewing operators across roles, observing live workflows, and mapping current-state processes that surface high-ROI opportunities for AI and automation
• Build the business case for each engagement: quantify the cost of the status quo, model expected ROI and prioritize a sequenced roadmap of automation opportunities the client can act on
• Design future-state workflows in detail: process diagrams, decision logic, exception handling, human-in-the-loop checkpoints, and integration touchpoints, all to a level of specificity engineering can build against
• Partner with an AI Engineer throughout the build, translating client requirements into technical specs, validating outputs against business intent, and brokering trade-offs (quality vs. speed vs. cost vs. risk) in plain language
• Lead change management on the client side: stakeholder alignment, communication plans, training rollout, and adoption tracking
• Own the client relationship end-to-end: scope, expectations, status updates, escalations, and executive readouts
• Serve as the single point of accountability for client outcomes
• Run post-deployment business reviews to measure realized impact, surface follow-on opportunities, and build the case for portfolio expansion
• Contribute internally by codifying reusable discovery frameworks, ROI models, workflow templates, and industry playbooks that scale across the practice.

AI Process Consultant

• Strategy — Refine the ICP, pricing model, and product positioning
• Customer Development — Lead pilots with practice owners and revenue cycle leaders, convert them to paid engagements, and build the go-to-market motion
• Product — Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback
• Capital — Lead the seed raise, supported by FutureSight's network and traction
• Team — Recruit and lead the founding team, and establish the cultural foundation of the company

Co-Founder, CEO – HealthTech, AI Revenue Recovery

• Drive customer adoption, usage, and renewal of Glia's AI features.
• Empower and enable our customers to grow their knowledge and appreciation of AI through the development and execution of training initiatives for client teams.
• Empower and enable our customers to drive adoption of Glia's AI features by their own end users.
• Implement AI products on time and on budget.
• Ensure that customers are achieving the desired business impact from Glia's AI features following implementation.
• Establish credibility with client stakeholders as an AI subject matter expert in relation to Glia's AI features.
• Provide pre-sales consultancy on AI features to assist our prospective clients in adopting Glia.
• Analyze AI performance metrics and provide data-driven recommendations for improvement.
• Provide assistance and best practices to clients on topics relating to prompt engineering and working with Generative AI.
• Serve as the primary technical advisor for AI-related inquiries and challenges.
• Offer guidance on Glia Virtual Assistant best practices to help clients leverage the full potential of the platform and optimize their conversational interactions with customers.
• Collaborate with Glia's product and engineering teams to communicate client feedback, feature requests, and identify areas for product improvement.
• Collaborate closely with implementation managers, solution architects, and implementation engineers as part of customer implementations.
• Document client processes and diagnose how Glia's AI products or integrations can improve efficiency and overall experience.

AI Consultant

• Own and maintain a pipeline of AI and automation use cases across People (lifecycle, Talent Acquisition, Total Rewards, Payroll, People Ops service, Workplace, and adjacent workflows).
• Prioritise initiatives based on impact, risk, feasibility, and alignment with People and business strategy, in partnership with People leadership and key stakeholders.
• Design and deploy agent-driven workflows that orchestrate complex, multi-step processes across systems and teams with minimal manual coordination (e.g., onboarding, offboarding, offer-to-hire, comp cycles, benefits/payroll events).
• Collaborate with the People Systems Architect to ensure underlying workflows, states, and data structures are agent-friendly (clear steps, owners, SLAs, and error paths).
• Implement robust monitoring, logging, and alerting for AI-enabled workflows so issues can be detected, investigated, and corrected quickly.
• Design decision-support agents that continuously analyse data and surface recommendations, scenarios, and risks to People and business leaders (e.g., comp change validations, hiring and headcount insights, risk patterns in tickets and lifecycle events).
• Partner with Data/BI to build and maintain dashboards underpinning these agents, with clear metrics and definitions.
• Establish review and override patterns so HRBPs and leaders own the decision logic while AI provides options, context, and risk flags.
• Design and implement always-on advisory agents that provide context-aware guidance to employees and managers on People topics, integrated into Slack, email, and internal portals, with clear escalation rules for high-stakes or complex cases.
• Reimagine how employees, managers, and People teams interact with People systems by embedding experiences into the flow of work (e.g., AI-powered nudges, in-Slack performance and feedback touchpoints, contextual prompts around key lifecycle events).
• Extend and enhance HRIS, ATS, compensation, and benefits tools through integrations, automation, and modern experience layers, rather than recreating functionality from scratch.
• Define and document AI guardrails: what agents can auto-decide vs where human review is required, and how fairness, compliance, and explainability are safeguarded.
• Work closely with IT, Security, Legal, and Data/BI to align AI implementations with data privacy, security, and regulatory requirements.
• Create reusable patterns, templates, and documentation so AI capabilities can be extended by the People team over time.
• Track KPIs for automations and agents (e.g., automation rates, time-to-resolution, error/rollback rates, satisfaction, time freed for People teams) and iterate based on real usage and feedback.

Senior People Systems, AI Specialist

• Support on strategic initiatives to deploy or leverage data and technology responsibly and ethically by providing expert advice to execute on TELUS’ data commitments
• Educate and advise business units on new or existing data uses and implementation of ethical technologies
• Conduct privacy and AI impact assessments, identify risks and provide corresponding recommendations
• Support the development of a data program that meets or exceeds the expectations of our customers while simultaneously ensuring TELUS’ ability to respectfully leverage data to deliver value to our stakeholders
• Collaborate with cross-functional stakeholders to develop and implement technology solutions and ensure adherence to the TELUS’ Trust Model
• Document, prioritize, and communicate clear privacy requirements for product initiatives and releases
• Escalate data risks promptly, with a sense of urgency, and recommend mitigating controls that are effective to protect the data of our customers and team members
• Adapt to meet the changing needs of the organization, and a fast-paced ambitious team, where priorities shift but the focus on the mission is steadfast

Data & Trust Manager – Privacy & AI

• Own deployments from zero to live - kick-off, automation setup, stakeholder alignment, and hitting the metrics that matter.
• Co-lead strategic accounts with senior team members, taking on responsibility progressively as you ramp.
• Apply your CX ops knowledge to diagnose why accounts are stuck: helpdesk configuration, ticket routing gaps, automation logic, escalation failures - and drive the fix.
• Keep every account you touch moving: daily updates, proactive escalations, clear documentation of progress and blockers.
• Manage customer expectations with confidence: hold timelines, push back when scope creeps, and keep relationships intact when things get hard.
• Shadow and support senior team members for the first 30 days, then take the lead on accounts.
• Feed operational patterns back to the product team: you see problems across accounts before anyone else does.

Deployment Manager, AI Agents

• Defining, leading, and evolving the VPTC AI strategy and roadmap (vision, priorities, and portfolio of use cases)
• Ensuring HR AI governance in alignment with the corporate AI@iA framework
• Supporting teams and senior leadership in identifying and prioritizing high–business-value HR AI use cases
• Acting as a strategic partner to HR leaders to support decision-making related to AI initiatives
• Promoting a value-driven approach focused on proof of value, adoption, and sustainable impact
• Conducting strategic and technology watch on AI, talent analytics, automation, and productivity tools
• Translating emerging trends into actionable opportunities for the organization
• Leading and providing functional leadership to the Digital Allies network
• Contributing to AI literacy, knowledge sharing, and the promotion of best practices through communities, workshops, and events

Practice Lead – HR Innovation, AI

• Support HR teams end to end—from ideation to proof of value, and through scaling when relevant.
• Support HR Centers of Expertise and VPTC teams in identifying, clarifying, and qualifying HR AI use cases.
• Assess relevance of use cases based on business value, feasibility, risks, and their technology integration zone (Zones 1, 2, and 3).
• Implement AI solutions, particularly in Zone 1 (citizen development – co-developing solutions with HR teams through expert guidance).
• Design, prototype, and test AI solutions applied to HR (assistants, automations, decision-support tools).
• Actively contribute to proofs of concept (POCs) and proofs of value (POVs).
• Collaborate closely with the IT Delivery Tower and systems teams on initiatives in Zones 2 and 3.
• Document technology choices, learnings, limitations, and impacts of developed solutions.
• Contribute to upskilling HR teams through coaching, knowledge transfer, and clear communication.
• Apply AI governance, security, ethics, and data protection frameworks.
• Contribute to the continuous improvement of the AI Innovation Hub’s practices.
• Document and share use cases, best practices, and learnings, and contribute to AI literacy initiatives.

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