AI Solutions Engineer, Technology Workplace Services

AI Enablement Business Analysis & Process Improvement (30%)

• Partner with TWS and business stakeholders to identify assess prioritize and document high-value AI automation and process-improvement opportunities.
• Analyze current-state workflows pain points controls dependencies exception paths data requirements and measurable improvement objectives.
• Determine whether AI workflow automation scripting process redesign or a non-technical change is the most appropriate response to a business or operational need.
• Translate business requirements into process designs solution requirements acceptance criteria test scenarios implementation plans support models and measurable success criteria.
• Develop use cases for ticket summarization triage routing response drafting knowledge retrieval trend analysis and service-quality checks.
• Maintain a prioritized AI and automation pipeline aligned with TWS objectives capacity risk tolerance and measurable business value.
• Gather user feedback identify adoption barriers and recommend process or solution improvements that increase usability and sustained value.

AI Engineering & Solution Development (40%)

• Design configure develop test deploy maintain and support secure scalable and maintainable AI-powered copilots agents automations scripts analytics and low-code solutions for TWS and digital workplace use cases.
• Build proof-of-concepts prototypes and production-ready solutions using approved platforms such as Microsoft Copilot Studio Azure AI Foundry Microsoft Fabric Power Platform APIs PowerShell Python and other sanctioned technologies.
• Develop enterprise search retrieval grounding orchestration agent and workflow solutions using approved TWS and enterprise knowledge sources.
• Create reusable prompts workflows templates connectors scripts integrations and solution components to improve consistency and accelerate delivery.
• Integrate AI capabilities with Microsoft 365 ServiceNow HR platforms collaboration tools endpoint asset identity reporting knowledge and operational workflow systems.
• Define grounding sources data mappings permission boundaries validation rules structured outputs and controls so solutions are accurate traceable and fit for purpose.
• Apply approved engineering practices for environment management configuration credentials source control testing release monitoring logging troubleshooting recovery rollback and retirement.
• Complete functional security privacy accessibility regression and user acceptance testing before production release.
• Create and maintain technical runbooks covering ownership dependencies access recovery rollback incident response monitoring support handoff and retirement.
• Collaborate with Architecture Security Privacy Risk Service Management Data platform teams and vendors to validate designs and address gaps before implementation.

AI Governance Risk & Responsible Use (15%)

• Ensure AI and automation solutions comply with approved architecture security privacy data governance records-management acceptable-use change-management audit accessibility and regulatory requirements.
• Perform preliminary risk and impact assessments and engage Information Security Privacy Risk Compliance Data Architecture or other control partners as required.
• Implement responsible AI controls including access management data protection auditability output validation exception handling escalation rollback and human oversight.
• Document solution purpose users data inputs processing logic outputs limitations risks dependencies controls approvals testing changes exceptions incidents and periodic reviews.
• Ensure AI-generated outputs and automated actions are validated and are not used as the sole basis for material operational or access decisions.
• Escalate material risks control failures data exposure inaccurate outcomes production issues and high-priority service impacts to the Manager TWS and appropriate partners.

Knowledge Management Adoption & Continuous Improvement (5%)

• Develop and maintain AI-assisted knowledge articles SOPs troubleshooting guides prompt guidance playbooks standards reference architectures job aids and support documentation.
• Validate AI-assisted content for accuracy clarity accessibility currency and alignment with approved processes before publication.
• Build AI literacy and adoption through demonstrations workshops training coaching knowledge sharing enablement programs and office-hour support.
• Advise teams on AI best practices prompt engineering output validation data handling responsible use solution design and automation opportunities.
• Monitor solution accuracy reliability security privacy cost efficiency adoption exceptions user satisfaction and business outcomes; implement improvements based on evidence and feedback.
• Develop dashboards metrics and reporting that demonstrate adoption quality productivity gains automation savings service improvements risk reduction and operational impact.

Technology Workplace Services Technology Support & Operational Continuity (10%)

• Provide targeted support for endpoints collaboration tools audio/visual equipment enterprise applications and related workplace technology services when required.
• Use operational knowledge to validate that AI-enabled improvements function effectively within TWS support processes and meet user needs.
• Manage assigned incidents requests problems and changes in accordance with ITIL practices documented procedures service expectations and escalation requirements.
• Assist with onboarding offboarding device deployment software rollout inventory and other TWS activities during priority events or coverage needs.
• Monitor and respond to production issues affecting AI-enabled workflows automations or related TWS services.

• College diploma or university degree in Information Technology Computer Science Business Technology Data and Analytics or a related discipline or equivalent experience.
• 5 or more years of experience in IT service delivery workplace technology AI enablement process improvement automation business analysis or a related technical role.
• Practical experience analyzing requirements and designing documenting testing deploying monitoring and supporting AI automation scripting analytics or low-code solutions.
• Working knowledge of generative AI and solution patterns including prompt design and orchestration retrieval-augmented generation enterprise search grounding structured output tool or function calling evaluation and human-in-the-loop controls.
• Familiarity with Microsoft 365 and approved enterprise AI and automation platforms including Microsoft Copilot Copilot Studio Power Automate Power Apps Power BI Microsoft Fabric Azure AI PowerShell APIs and related tools used by the Bank.
• Knowledge of API integration authentication and authorization managed identities or service accounts secrets management data transformation secure connector design source control solution packaging environment configuration release management monitoring logging and technical runbooks.
• Understanding of ITIL practices including Incident Request Problem Change Knowledge Asset and Service Level Management.
• Strong knowledge of security privacy data lifecycle governance classification minimization access retention lineage appropriate use and AI evaluation principles.
• Strong analytical troubleshooting documentation communication collaboration prioritization and change-adoption skills with the ability to evaluate effort dependencies risk business value and technical trade-offs.
• Commitment to continuous learning as AI technologies engineering practices security expectations and regulatory requirements evolve.