About the role

Full-Stack Software Engineer developing edge-native software for decentralized grid operations. Collaborating on intelligent control systems bridging physics, AI, and distributed computing.

Responsibilities

Build and deploy edge-native software components for decentralized operation, sensing, and control.
Develop federated data pipelines that allow distributed nodes to collaborate securely without central coordination.
Develop and deploy robust virtual sensing algorithms to infer critical power grid parameters (e.g., voltage stability, phase angles, line temperature, asset health) from limited sensor data available at the grid edge.
Deploy adaptive edge intelligence and control logic at the edge, enabling real-time grid intelligence with minimal latency and network.
Collaborate with power systems engineers to validate virtual sensor accuracy against physical models and real-world data from substations, field devices, and peer sensors.
Integrate field data sources (SCADA, PMUs, DER controllers) and IoT protocols/networks (LoRa, MQTT, DNP3, Modbus).
Support experimentation and prototyping in simulation environments and customer’s test sites.
Collaborate with systems and data engineers to close the loop between simulation and live operations.
Collaborate with cross-functional teams to integrate AI/ML capabilities, federated control frameworks, and digital twins into next-generation grid platforms.
Work closely with data scientists, control engineers, infrastructure specialists and Customers, to integrate software with physical grid systems.

Working experience with Transmission and distribution , and federated architectures, and resilient edge software.
Strong skills in script writing using MATLAB, Go, Rust, Python (backend/edge) and HTML, CSS, TypeScript/React or Angular(UI).
Deep Experience with Kubernetes/K3s, Kafka/NATS, MQTT, gRPC, PulsarInfluxDB/TimescaleDB, and observability stacks (Prometheus, Grafana).
Solid understanding of control theory and signal processing techniques for application in virtual sensing systems, such as Kalman filters or other state estimation methods.
Experience in integrating virtual sensor outputs into existing control loops for real-time monitoring, process optimization, and predictive maintenance applications.
Ability to evaluate and test the performance and reliability of developed virtual sensors.
Skilled in interpreting complex sensor data outputs and translating insights into actionable virtual sensor models.
Work experience with Digital Twin / Simulation modeling: OpenFMB, Modelica, graph-based modeling) and AI/ML model algorithms.
Hands-on work with AI/ML models in production environments.
Work experience in federated architectures, and resilient edge software applied to Transmission & Distribution application.

medical, dental, vision, and prescription drug coverage
access to Health Coach from GE Vernova, a 24/7 nurse-based resource
access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services
GE Vernova Retirement Savings Plan
tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions
access to Fidelity resources and financial planning consultants
tuition assistance
adoption assistance
paid parental leave
disability benefits
life insurance
12 paid holidays
permissive time off