Software Engineer – AI Backend & Agent Frameworks

Job Description Summary

About This Role - The power grid is changing and the software behind it needs to change faster. As a Staff Software Engineer on GE Vernova's Applied Grid Innovation team, you'll build the backend platforms and artificial intelligence (AI) agent frameworks that make next-generation grid management possible. Your work will directly shape how grid operators make decisions, automate complex workflows, and maintain reliable energy delivery s is a senior individual contributor role for an engineer who thrives on system architecture challenges and wants their code running in production environments where reliability isn't optional.

• Design and build distributed backend systems using Python, Java, C++, or Go - creating scalable microservices, APIs, and event-driven architectures that integrate with operational grid systems including Supervisory Control and Data Acquisition (SCADA), Phasor Measurement Unit (PMU) data streams, and time-series databases.
• Architect AI agent frameworks that orchestrate machine learning (ML) models, rule engines, simulation engines, and enterprise grid services - enabling intelligent automation and decision support in control room environments.
• Develop AI/ML production infrastructure, including model lifecycle management, inference services, agent coordination layers, and real-time feedback loops for Advanced Energy Management Systems (AEMS), Advanced Distribution Management Systems (ADMS), and Wide Area Monitoring Systems (WAMS).
• Lead code quality and engineering excellence, including automated testing, Continuous Integration/Continuous Deployment (CI/CD) pipeline development, performance tuning, and system observability.
• Collaborate across disciplines - working alongside data scientists, power systems engineers, and Dev Ops teams to bring AI-driven solutions from prototype to production in mission-critical environments.
• Contribute to architecture decisions with a focus on scalability, fault tolerance, cybersecurity, and suitability for on-premises control center deployments.

You're an experienced backend engineer who combines deep systems architecture expertise with hands-on experience delivering AI/ML infrastructure in production - and you're ready to apply that expertise to one of the world's most critical infrastructure domains.

• 5+ years of professional experience in backend or distributed systems development.
• Proficiency in Python and at least one additional backend language (Java, C++, or Go).
• Proven experience designing microservices, REST/gRPC APIs, and event-driven architectures.
• Hands-on experience building AI/ML production systems - including model serving, inference pipelines, or agent-based orchestration frameworks.
• Experience with AI/ML frameworks such as Tensor Flow, PyTorch, or Scikit-learn.
• Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines.
• Strong understanding of software architecture, concurrency, system performance, and security principles.

• Experience developing software for on-premises, mission-critical, or operational technology (OT) control environments.
• Working knowledge of Energy Management Systems (EMS), Distribution Management Systems (DMS), WAMS, SCADA, or power system operations.
• Familiarity with time-series data systems and high-throughput data processing pipelines.

A formal education and subsequent Bachelor's, Master's, or PhD in Computer Science, Software Engineering, or a related field is nice to have, but we are most interested in your total experience and professional achievements.

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