Job Description Summary

GE Vernova is seeking a Staff AI Engineer to build and scale AI-native systems that power intelligent automation across AEMS, ADMS, and DERMS applications. This is a deeply hands-on technical role focused on designing, coding, deploying, and operating production-grade AI agent platforms in mission-critical grid environments.
You will architect and implement multi-agent systems, model-serving infrastructure, and distributed backend services that integrate real-time grid data, optimization engines, and AI reasoning capabilities.

Job Description

Roles & Responsibilities:

• Design and personally implement core components of AI agent frameworks, including orchestration engines, tool integration layers, and state management systems.

• Build production-grade backend services in Python (and/or Java, C++, Go) to support AI inference, workflow automation, and real-time grid analytics.

• Develop and deploy LLM-powered agents with structured prompting, tool usage, guardrails, and memory mechanisms.

• Implement model serving infrastructure, including inference APIs, batching strategies, performance tuning, and monitoring.

• Write scalable microservices and event-driven components that ingest and process high-volume time-series data.

• Integrate AI services with SCADA, PMU, simulation engines, contingency analysis tools, and operational data platforms.

• Optimize system performance for low-latency decision support in control center environments.

• Build CI/CD pipelines, automated tests, and observability tooling for AI services.

• Develop explainability, logging, and traceability mechanisms for AI-generated recommendations or actions.

• Troubleshoot production issues across distributed AI systems and drive performance and reliability improvements.

• Conduct deep code reviews and actively contribute high-quality code to shared repositories.

Education & Qualifications:

• Master’s or PhD in Computer Science, AI/ML, or related field.

• 8+ years of hands-on software development experience, with significant backend engineering depth.

• Demonstrated experience building and deploying AI/ML systems into production (not just experimentation).

• Strong proficiency in Python and experience building backend systems in Java, C++, or Go.

• Experience implementing LLM integrations, prompt orchestration, agent tooling, or multi-step AI workflows.

• Deep understanding of distributed systems, concurrency, APIs, and microservices architecture.

• Experience building model serving pipelines and inference systems (REST/gRPC, async processing, streaming).

• Experience with containerization and orchestration (Docker, Kubernetes).

• Strong debugging and performance optimization skills in distributed environments.

• Experience working with time-series or streaming data systems.

• Familiarity with EMS, DMS, WAMS, SCADA, or power system applications is highly desirable.

• Proven track record of shipping reliable, secure, high-performance systems in production environments.

GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).

Relocation Assistance Provided: Yes

 

 

For candidates applying to a U.S. based position, the pay range for this position is between $151,800.00 and $227,700.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.

 

 

Bonus eligibility: discretionary annual bonus.

 

 

This posting is expected to remain open for at least seven days after it was po