AI Enablement Engineer – Intake, Value & Adoption

Project description

The AI Use Case Intake & Value Lead owns the front door of the bank's AI program: the use-case intake framework, stage gates, prioritization methodology, and value/ROI measurement that determine what the bank builds, in what order, and with what expected return. This role converts governance principles into a practical, repeatable intake process that business teams can navigate, and gives leadership a defensible, data-driven view of the AI portfolio.

This is an engineering seat, not an analyst seat: the role builds the intake and portfolio tooling itself (workflow automation, GenAI-assisted intake screening, usage-data integration for value tracking), technically evaluates proposed use cases against platform capabilities and constraints, and constructs value measurement from real platform telemetry — leveraging GenAI capabilities to automate the intake and reporting machinery rather than operating it manually.

Responsibilities

• Intake Framework & Portfolio Management
• Design, implement, and operate the enterprise AI use-case intake framework: submission, screening, risk-tier alignment, stage gates, and approval workflow integrated with governance and platform onboarding.
• Define intake requirements and templates (business case, data classification, oversight model, success criteria) that satisfy governance without overburdening business teams.
• Maintain the AI use-case portfolio and pipeline as a managed system of record, with stage, status, ownership, and risk posture visible to leadership.
• Facilitate intake reviews and prioritization forums with business sponsors, governance, and platform stakeholders.
• Value, ROI & FinOps Alignment
• Build and maintain the ROI and value-measurement methodology for AI use cases: baseline capture, benefit hypotheses, realized-value tracking, and total cost of ownership including model usage and platform consumption.
• Partner with the observability/FinOps function to connect actual usage and spend data to the business cases that justified each use case.
• Produce portfolio-level reporting for leadership: value delivered, adoption, cost trends, and prioritization recommendations.
• Develop benefit-realization checkpoints into the use-case lifecycle so value claims are validated, not just projected.
• Business Partnership & Enablement
• Serve as the primary intake partner for business lines bringing AI use cases forward; coach sponsors and analysts through requirements, business cases, and gate readiness.
• Translate between business intent and technical delivery: work with solution architecture and platform engineering to shape feasible, governed solutions.
• Provide work direction and quality review to business analysts and developers supporting use-case documentation.
• Drive awareness and adoption of the intake process across business lines: communications, onboarding sessions, and sponsor enablement so the funnel fills by design rather than by chance.
• Continuously improve the intake process based on cycle-time, sponsor feedback, and governance findings.

Skills

Must have

• Bachelor's degree and a minimum of 5 years' experience in business systems analysis, product/portfolio management, or technology program analysis, or in lieu of a degree, a combined minimum of 9 years' education and/or relevant work experience.
• Demonstrated experience designing and operating intake, demand-management, or stage-gate processes for technology initiatives — with the technical depth to evaluate AI feasibility, platform fit, and consumption economics directly.
• Strong financial and value analysis skills: business cases, ROI modeling, cost/benefit tracking, and executive reporting.
• Working technical fluency with AI/GenAI concepts, consumption-based cost models, and enterprise delivery lifecycles (SDLC/Agile).
• Strong facilitation, communication, and stakeholder management skills across business and technology audiences.
• Advanced proficiency with analysis and reporting tools (Excel, Power BI or equivalent).

Nice to have

• Experience with AI/GenAI portfolio management, FinOps concepts, or usage-based cost allocation.
• Experience in financial services or another highly regulated industry.
• Familiarity with governance and risk processes (risk tiering, data classification, third-party risk).
• Experience with workflow/intake tooling (ServiceNow, Jira, or equivalent).