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Lead Artificial Intelligence Specialist

Duke Energy
relocation assistance
United States, North Carolina, Charlotte
Jul 25, 2025
More than a career - a chance to make a difference in people's lives.

Build an exciting, rewarding career with us - help us make a difference for millions of people every day. Consider joining the Duke Energy team, where you'll find a friendly work environment, opportunities for growth and development, recognition for your work, and competitive pay and benefits.

Job Summary

This role offers a unique opportunity to apply cutting-edge optimization techniques to real-world energy planning problems, driving innovation and efficiency across Duke Energy's grid investment strategy.

Position Summary: AI Specialist - Grid Investment Optimization

We are seeking a highly motivated AI Specialist with strong experience in meta-heuristic algorithms, Mixed-Integer Linear Programming (MILP), and Python-based optimization to support advanced grid investment planning at scale. This role is ideal for professionals who thrive at the intersection of data science, optimization modeling, and energy systems planning.

AI Specialists at Duke Energy play a pivotal role in designing and deploying adaptive optimization models that address complex, non-linear, and combinatorial planning challenges. These models incorporate real-world constraints such as capacity thresholds, investment budgets, and evolving regulatory mandates. The ideal candidate will be passionate about building scalable, flexible optimization tools that directly influence strategic investment decisions.

Key Responsibilities
  • Design and implement meta-heuristic and MILP-based optimization models in Python for grid investment planning.

  • Prototype and evaluate algorithms like Genetic Algorithms (GA), Harmony Search, and MILP to solve large-scale, non-linear, constrained optimization problems.

  • Collaborate with cross-functional teams to understand investment criteria, shifting priorities, and regulatory mandates.

  • Ensure models are adaptable and scalable, enabling flexibility for new constraints without re-architecting core logic.

  • Conduct exploratory data analysis and preprocessing to prepare model inputs.

  • Integrate models with Duke Energy's analytics ecosystems (e.g., PowerBI, Tableau, Excel) to streamline result interpretation.

  • Facilitate hands-on workshops with business users, covering:

  • Model configuration and setup

  • Input data preparation

  • Interpretation of optimization results

  • Interpret and articulate optimization model outputs to non-technical stakeholders, translating complex results into actionable business insights.

  • Mentor team members in both professional and technical development.

  • Ensure AI compliance with cybersecurity, cloud architecture, and enterprise standards.

  • Participate in Communities of Practice (AI, Cloud, Architecture) and contribute to innovation discovery.

Required/Basic Qualifications
  • Associate's degree and 7 years of related work experience

  • In lieu of an Associate's degree, a High School diploma/GED and 9 years of related work experience

Desired Qualifications
  • Bachelor's degree in Engineering, Computer Science, Operations Research, or related field

  • Strong knowledge of Artificial Intelligence and Machine Learning techniques including classification, regression, and neural networks

  • Experience working with Data Scientists and AI teams in an enterprise environment

  • Previous experience contributing to Duke Energy AI initiatives

  • Strong communication skills and ability to translate technical concepts to business stakeholders

  • Demonstrated ability to lead and mentor technical teams

Working Conditions
  • Hybrid Mobility Classification - Work will be performed from both remote and onsite locations after the onboarding period. Employees should live within a reasonable daily commute to a Duke Energy facility.

  • Office job environment, day shift

Travel Requirements

Not required Relocation Assistance Provided (as applicable)No Represented/Union PositionNo Visa Sponsored PositionNo

Posting Expiration Date

Tuesday, July 29, 2025

All job postings expire at 12:01 AM on the posting expiration date.

Please note that in order to be considered for this position, you must possess all of the basic/required qualifications.

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