Sr. Principal Engineer

Job Description

We are seeking a Senior Principal Engineer to lead advanced AI‑driven optimization initiatives for complex logistics systems. This role is responsible for designing, modeling, and solving large‑scale optimization problems that directly impact operational efficiency, cost, and scalability across logistics and supply‑chain applications.

The ideal candidate combines deep academic rigor in optimization with hands‑on industrial implementation experience, and can act as both a technical authority and architect for optimization‑based AI solutions.

Key Responsibilities

• Lead the design and implementation of optimization models for large‑scale logistics and supply‑chain problems (e.g., routing, scheduling, network design, capacity planning).
• Develop and maintain optimization formulations using Python‑based modeling frameworks such as: Gurobi / GurobiPy Pyomo
• Select, implement, and tune appropriate optimization algorithms, including: Linear Programming (LP) Mixed‑Integer Linear Programming (MILP) Non‑Linear Programming (NLP)
• Translate complex real‑world logistics constraints into mathematically rigorous and computationally efficient models.
• Collaborate with AI, data science, and system engineering teams to integrate optimization engines into production AI platforms.
• Evaluate solver performance and scalability; optimize model performance for real‑time or near‑real‑time decision‑making.
• Provide technical leadership, mentoring, and design reviews for optimization engineers and researchers.
  
  

Required Qualifications

• PhD in Optimization, Operations Research, Applied Mathematics, Industrial Engineering, or a closely related field.
• Deep expertise in mathematical optimization modeling and algorithmic design.
• Strong hands‑on experience with: Gurobi / GurobiPy Pyomo
• Proven knowledge of and practical experience with: LP, MILP, and NLP formulations Solver behavior, numerical stability, and computational complexity
• Strong understanding of logistics and supply‑chain optimization problems
• Advanced Python programming skills for model development and integration.
  
  

Preferred (Nice‑to‑Have) Qualifications

• Experience applying optimization techniques in autonomous systems, including: Motion planning Trajectory optimization Autonomous vehicle or robotics applications
• Familiarity with hybrid approaches combining optimization and machine learning.
• Experience deploying optimization‑based decision engines in production environments.
  
  

Nextpower offers a comprehensive benefits package. We provide health care coverage, dental and vision, 401(K) participation including company matching, company paid holidays with unlimited paid time off, generous discretionary company bonuses, life and disability protection and more. Employees in certain positions may be eligible for stock compensation. All plans are in accordance with relevant plan documents. For more information on Nextpower 's benefits please view our company website at www.nextpower.com. Pay is based on market location and may vary based on factors including experience, skills, education and other job-related reasons. The annual salary range for this position is $275,000-$300,00.

At Nextpower, we are driving the global energy transition with an integrated clean energy technology platform that combines intelligent structural, electrical, and digital solutions for utility-scale power plants. Our comprehensive portfolio enables faster project delivery, higher performance, and greater reliability, helping our customers capture the full value of solar power. Our talented worldwide teams are redefining how solar power plants are designed, built, and operated every day with smart technology, data-driven insights, and advanced automation. Together, we’re building the foundation for the world’s next generation of clean energy infrastructure.

Nextpower is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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