AI Enablement Engineer
AI Enablement Engineer
Posted yesterday
SENIORITY
Lead
About the role
- Design, implement, and operate the enterprise AI use-case intake framework, including 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)
- Maintain the AI use-case portfolio and pipeline as a managed system of record
- Facilitate intake reviews and prioritization forums with business sponsors, governance, and platform stakeholders
- Build and maintain the ROI and value-measurement methodology for AI use cases, including baseline capture, benefit hypotheses, and realized-value tracking
- Partner with the observability/FinOps function to connect usage and spend data to business cases
- Produce portfolio-level reporting for leadership on value delivered, adoption, cost trends, and prioritization recommendations
- Develop benefit-realization checkpoints into the use-case lifecycle
- Serve as the primary intake partner for business lines bringing AI use cases forward, coaching sponsors through requirements and gate readiness
- Translate between business intent and technical delivery, working with solution architecture and platform engineering
- 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 through communications and enablement sessions
- Continuously improve the intake process based on cycle-time, sponsor feedback, and governance findings
- Mandatory Skills
- Bachelor's degree and 5+ years' experience in business systems analysis, product/portfolio management, or technology program analysis (or 9 years combined education/relevant work experience in lieu of degree)
- Demonstrated experience designing and operating intake, demand-management, or stage-gate processes for technology initiatives, with technical depth to evaluate AI feasibility, platform fit, and consumption economics
- Strong financial and value analysis skills — business cases, ROI modeling, cost/benefit tracking, 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 Skills
- 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)
Before you apply
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Your profile is current
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Two examples you can talk through
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A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
