Job Title: AI Enablement Engineer Intake, Value & Adoption
Location: Remote (there will be a business trip or initial few times per year in Buffalo, NY and client will take care of the expenses)
Long term
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.
Must have Skills:
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).
