Manager of AI & Analytics Engineering

NextEra Energy

41d

About The Position

NextEra Analytics offers energy consulting services using industry-leading scientific analysis for planning, siting, forecasting and optimizing all forms of energy projects. Our optimization and analytics platforms integrate open-source technologies to leverage massive, diverse sets of utility operating data. This enables rapid development of operational solutions. Applying expertise in advanced mathematics, data and physical sciences, we solve some of the hardest problems facing the energy industry. Position Specific Description We are seeking a proven engineering leader who is passionate about artificial intelligence, advanced analytics, and building scalable data systems that accelerate clean energy innovation. The ideal candidate blends deep technical expertise with strong leadership, an engineering-first mindset, and a track record of driving complex initiatives from concept to production. You have demonstrated the ability to build high-performing teams, mentor technical talent, launch new capabilities, and lead transformative AI/ML and data engineering programs. This role reports directly to the Sr. Director of AI & Analytics for NextEra Analytics and will lead the design, development, and deployment of enterprise AI and analytics solutions across the NextEra family of businesses. You will oversee engineering execution, establish best practices, shape technical strategy, and ensure delivery of reusable, production-grade AI capabilities. Successful candidates thrive in a fast-paced, entrepreneurial environment that values innovation, precision, and enterprise-scale impact. We look for leaders who are strong problem solvers, excellent communicators, and deeply committed to technical excellence. Our team is committed to building successful careers. You will guide a talented group of engineers and data scientists working on critical AI/ML, platform engineering, and analytics initiatives that influence NextEra’s future.

Requirements

Bachelor’s Degree
Experience: 8+ years
Supervisor/Management Experience: 3+ years

Nice To Haves

Experience with modern statistical, machine learning, and AI approaches (classification, regression, feature engineering, optimization, deep learning, and foundation models)
Programming skills enabling oversight of end-to-end engineering work (Python required; SQL, Scala, and R a plus)
Experience with large datasets and distributed computing technologies (Spark, Hive/Hadoop, Ray, or cloud-native equivalents)
Experience with contemporary AI frameworks, including both traditional ML and Generative AI (scikit-learn, PyTorch, TensorFlow, Spark MLlib, Hugging Face Transformers, LangChain, LlamaIndex, DSPy)
Familiarity with LLMOps and AI system development (prompt engineering, retrieval-augmented generation, evaluation frameworks, vector databases)
Experience working with agentic or autonomous AI frameworks and multi-agent orchestration (e.g., LangGraph, CrewAI, or similar tools)
Knowledge of statistical techniques, experimental design, and model evaluation methodologies
Ability to present complex technical information and insights to executives, cross-functional teams, and non-technical stakeholders using modern visualization tools (e.g., Plotly, Power BI, Tableau)
Master’s Degree

Responsibilities

Lead teams in developing AI, machine learning, and analytical solutions for high-value business problems
Architect and oversee scalable data pipelines, model pipelines, and distributed systems across cloud and on-prem environments
Establish engineering best practices for production AI systems, including code quality, CI/CD, observability, and documentation
Guide teams in optimizing performance of models, applications, and AI-driven workflows
Evaluate and incorporate third-party and external data sources to enhance enterprise analytics
Review and refine ad-hoc analyses and insights before presenting them to senior leadership and business stakeholders
Oversee full lifecycle model deployment—from prototyping through hardened, production-grade implementation
Drive adoption of reusable internal platforms, agentic AI frameworks, and enterprise AI/ML tools
Develop talent through mentorship, coaching, and fostering a strong engineering culture
Draws insights from data and makes recommendations
Conducts data analytics to support key business unit initiatives
Develops predictive models
Oversees data strategy and governance for business unit
Monitors end-to-end business processes data for opportunities to improve
Provides support to the business on the use of data analytics tools
Performs other job-related duties as assigned