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Operations Analyst Lead - AI & ML

Job in Taylor, Williamson County, Texas, 76574, USA
Listing for: ERCOT
Full Time position
Listed on 2026-07-25
Job specializations:
  • IT/Tech
    AI Business & Operations, IT Business Analyst, AI Engineer (Applied/Software), Change Management
Salary/Wage Range or Industry Benchmark: 160000 - 220000 USD Yearly USD 160000.00 220000.00 YEAR
Job Description & How to Apply Below

At ERCOT, our diverse and dynamic work environment provides a platform on which employees can work together to build the future of the Texas power grid and wholesale market utilizing the latest technologies and resources. We encourage you to join our talented, dedicated workforce to develop world‑class solutions for today and tomorrow's energy challenges while learning new skills and growing your career.

ERCOT is committed to fostering inclusion at all levels of our company. It is the cornerstone of our corporate values of accountability, leadership, innovation, trust, and expertise. We know that individuals with a wide variety of talents, ideas, and experiences propel the innovation that drives our success. An inclusive and diverse workforce strengthens us and allows for a collaborative environment to solve the challenges that face our industry today and in the future.

JOB

SUMMARY

The AI & ML Operations Analyst Lead drives the adoption and responsible use of AI across the organization. The role partners with department leaders and staff to identify opportunities, coordinate the intake and prioritization of AI use cases, and enables the workforce through training, a champions network, and a community of practice. This position also focuses on transparency and quality by developing monitoring, dashboards, and reporting that give leadership and the broader enterprise visibility into AI usage, value, and impact.

The role has a focus on practical outcomes over experimentation and operates within ERCOT's AI governance framework. This is an enablement role, not an engineering role.

JOB DUTIES Driving Adoption and Measurable Outcomes
  • Drive meaningful adoption of AI across the organization, moving the broader organization toward confident, productive use of AI tools.
  • Track adoption metrics, usage patterns, and workflow impact to evaluate the effectiveness of AI implementations, and report findings to leadership.
  • Develop and maintain dashboards that give visibility into AI usage, value, and impact.
  • Establish and report on expected value, business outcomes, and success measures for AI initiatives, in alignment with governance expectations.
Department Discovery and Business Process Analysis
  • Partner with department leaders and staff to map current workflows, identify inefficiencies, and surface high value opportunities where AI can reduce manual effort, improve quality, or accelerate outcomes.
  • Translate business needs into clear requirements for AI solutions, serving as the bridge between non-technical staff and technology capabilities.
Intake, Backlog, and Governance Coordination
  • Operate the intake process for AI applications and requests, ensuring submissions are captured, triaged, and tracked.
  • Manage the AI backlog, prioritizing items against organizational value, risk, and readiness.
  • Prepare use cases for risk tiering and review by the appropriate governance body, and support registration of AI capability in the AI System Registry.
  • Coordinate with technical, governance, security, and architecture functions to move items through the pipeline.
  • Ensure AI System Registry is updated and current.
Community and Champions Network
  • Manage the AI community of practice, including meeting cadence, agendas, content, and follow ups.
  • Build and sustain the AI champions network across business units, equipping champions to support adoption locally.
  • Surface use cases, questions, and friction points from the community and route them to the right owners.
  • Provide and support coaching and office hours to help staff embed AI into their daily routines.
Platform and Feature Monitoring
  • Monitor new features, models, and capabilities released across approved AI platforms such as Claude and ChatGPT.
  • Evaluate and pilot AI tools and features against organizational needs, security requirements, and governance standards.
  • Maintain awareness of platform changes that affect cost, security posture, or governance requirements, and communicate what matters in plain language.
Training and Enablement
  • Tap into the needs of the organization and transparently provide the tooling, guidance, and resources people require.
  • Create internal enablement resources such as quick…
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