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Open nowFirst seen 35 hours ago

AI Enablement Engineer

Glint Tech Solutions LLC139 open roles

Where
Buffalo, New York, United States
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Your applicationOpen nowAI Enablement EngineerGlint Tech Solutions LLC · Buffalo, New York, United States

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This job: first seen 35 hours ago

The posting

Job Title: AI Enablement Engineer

Location: Remote within the USA, or onsite in Buffalo, NY / Wilmington, DE (client preference for candidates near these areas). New hires are required to work onsite at the client's office for the first 2–3 weeks (treated as a business trip; travel expenses covered by the company).

Company Overview

Glint Tech Solutions is a women-owned, global IT staffing and recruiting firm serving enterprise clients across the USA and Canada.

Project Description

A leading financial services client is seeking an AI Use Case Intake & Value Lead who will own 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 is an engineering 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.

Key Responsibilities

  • 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)
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