About this role
GE Vernova seeks a hands-on senior architect to own AI-assisted Services solutions across its Grid Software portfolio. The role combines enterprise AI architecture with practical guidance for global teams running multiple projects, establishing disciplined, production-ready AI workflows that improve software delivery and provide value to utility customers.
Responsibilities
- Design and maintain enterprise AI reference architectures and reusable components for agentic workflows, RAG knowledge systems, time-series forecasting and computer vision. Set standards for data ingestion, deployment, monitoring, versioning and lifecycle management, aligned with enterprise platforms and approved tools.
- Establish AI design practices, architecture reviews, decision records and documentation standards. Add review checkpoints to the portfolio stage-gate process and guide teams on scalability, security, maintainability and reuse across subsystems.
- Integrate AI-assisted workflows into Services standard work and quality management processes. Define how AI-generated outputs are reviewed and validated, and support updated documentation, training and process guidance.
- Partner with Digital/IT, ARC Foundry and platform teams on MLOps, LLMOps, integrations and toolchain standards. Address training pipelines, deployment automation, performance monitoring, drift detection and retraining governance; evaluate platform and vendor options and guide use of AMP, AWS, Azure and enterprise infrastructure.
- Mentor AI architects, lead technical forums and advise complex or high-risk initiatives. Contribute to governance reviews and assessments of model risk, data integrity, cybersecurity and auditability.
Required qualifications
At least 15 years of hands-on software development experience, technical architecture and work with large-scale enterprise systems. A bachelor’s degree in services, Computer Science, Applied Mathematics, Data Science or a related technical field is required; an advanced degree is strongly preferred. Candidates need hands-on experience building and deploying AI/ML solutions and defining enterprise-level architecture, expertise with frameworks such as TensorFlow, PyTorch and Scikit-learn, and knowledge of LLMs, SLMs, diffusion models, GANs, supervised and deep learning, time-series analysis, agentic workflows and physics-informed modeling. Familiarity with MLOps, cloud AI infrastructure, model serving and enterprise data platforms is required.
Preferred characteristics: Experience with industrial Services applications such as predictive maintenance, anomaly detection and AI-assisted validation; familiarity with n8n, LangGraph or CrewAI and multi-agent architectures; mentoring distributed teams; and strong communication, stakeholder collaboration and Lean process-improvement skills. The position is listed in Hyderabad and Bangalore, India. Relocation assistance is provided.