GlobalLogic is looking for an analytical Power System Software Engineer. This role focuses on application of software engineering to grid Reliability, Security

Assessment, and High- Performance Simulation. You will work on the technical core of utility operations. Your task is to lead a team that is tasked to modernize and accelerate computational tools. You will develop new techniques, use parallel programming, high-performance computing (HPC), and artificial intelligence to improve these tools.

Key Responsibilities

● Team Lead: Manage the workflow of a small team. Coordinate technical tasks among engineers to ensure the success of the project, mentor and develop the team

● Reliability and Security Modelling: Build software modules for real-time and operational planning. These modules include Power Flow, Optimal Power Flow

Contingency Analysis (N-1, N-2 criteria), Voltage Stability (VSAT), and

Transient Stability (TSAT) and others.

● Simulation Acceleration: Create methods to speed up simulations and static analysis tools.

● HPC and Parallel Computing: Use parallel processing, multi-threading, CUDA and other frameworks. You will apply distributed computing patterns to evaluate many contingencies at the same time.

● AI for Reliability: Train and use Physics-Informed Neural Networks (PINNs) or surrogate ML models. These models must evaluate system stability margins and predict voltage or frequency collapse quickly.

● Cross-Functional Collaboration: Work with platform architects to provide low-latency analytics tools.

● Software Craftsmanship: Write clean code and keep documentation quality high. Use version control (Git), perform code reviews, and use containerized deployment.

Must-Have Skills

● Education: You must have a Ph.D. degree in Electrical Engineering, Computer

Science, or Applied Mathematics. Your research focus should be on Power

System or graph based analysis, operational research or optimization.

● Domain Expertise: You need a solid understanding of power system dynamics, transient and voltage stability, and numerical integration. You will have built software tools that implement such algorithms.

● Programming and Architecture: You must be proficient in programming such as golang, Rust, C/C++ or Python. You need a solid understanding of Data

Structures and Algorithms (DSA), sparse matrix calculations, and parallel programming like OpenMP,



MPI, or CUDA.

● People Management: You must have experience in managing workflows and coordinating technical tasks, leading agile ceremonies and setting up software best practices. You must be able to mentor and develop engineers.

● Domain Tools: You must have hands-on experience with an industry-standard power system simulation tool. You must be able to integrate these tools into automated software workflows.

● AI/ML Production: You must have experience developing Machine Learning

(ML) algorithms into production-grade systems.

Nice-to-Have Skills

● Domain Tools: Experience with tools like DSATools, PSS/E, or DIgSILENT

PowerFactory or open-source tools is beneficial.

● AI/ML Production: Use of Machine Learning (ML) or Deep Learning architectures in production grade systems is beneficial.

● Technical Stack: Gurobi, CPLEX, JuMP, Pyomo, Pandas, NumPy, and ML frameworks (PyTorch or TensorFlow) are beneficial.

Job Responsibilities

GlobalLogic is looking for an analytical Power System Software Engineer. This role focuses on application of software engineering to grid Reliability, Security

Assessment, and High- Performance Simulation. You will work on the technical core of utility operations. Your task is to lead a team that is tasked to modernize and accelerate computational tools. You will develop new techniques, use parallel programming, high-performance computing (HPC), and artificial intelligence to improve these tools.

Key Responsibilities

● Team Lead: Manage the workflow of a small team. Coordinate technical tasks among engineers to ensure the success of the project, mentor and develop the team

● Reliability and Security Modelling: Build software modules for real-time and operational planning. These modules include Power Flow, Optimal Power Flow

Contingency Analysis (N-1, N-2 criteria), Voltage Stability (VSAT), and

Transient Stability (TSAT) and others.

● Simulation Acceleration:



Create methods to speed up simulations and static analysis tools.

● HPC and Parallel Computing: Use parallel processing, multi-threading, CUDA and other frameworks. You will apply distributed computing patterns to evaluate many contingencies at the same time.

● AI for Reliability: Train and use Physics-Informed Neural Networks (PINNs) or surrogate ML models. These models must evaluate system stability margins and predict voltage or frequency collapse quickly.

● Cross-Functional Collaboration: Work with platform architects to provide low-latency analytics tools.

● Software Craftsmanship: Write clean code and keep documentation quality high. Use version control (Git), perform code reviews, and use containerized deployment.

Must-Have Skills

● Education: You must have a Ph.D. degree in Electrical Engineering, Computer

Science, or Applied Mathematics. Your research focus should be on Power

System or graph based analysis, operational research or optimization.

● Domain Expertise: You need a strong understanding of power system dynamics, transient and voltage stability, and numerical integration. You will have built software tools that implement such algorithms.

● Programming and Architecture: You must be proficient in programming such as golang, Rust, C/C++ or Python. You need a solid understanding of Data

Structures and Algorithms (DSA), sparse matrix calculations, and parallel programming like OpenMP, MPI, or CUDA.

● People Management: You must have experience in managing workflows and coordinating technical tasks, leading agile ceremonies and setting up software best practices. You must be able to mentor and develop engineers.

● Domain Tools: You must have hands-on experience with an industry-standard power system simulation tool. You must be able to integrate these tools into automated software workflows.

● AI/ML Production: You must have experience developing Machine Learning

(ML) algorithms into production-grade systems.

Nice-to-Have Skills

● Domain Tools: Experience with tools like DSATools, PSS/E, or DIgSILENT

PowerFactory or open-source tools is beneficial.

● AI/ML Production: Use of Machine Learning (ML) or Deep Learning architectures in production grade systems is beneficial.

● Technical Stack: Gurobi, CPLEX, JuMP, Pyomo, Pandas, NumPy, and ML frameworks (PyTorch or TensorFlow) are beneficial.

📌 Technical Lead (Noida)
🏢 GlobalLogic
📍 Noida