Senior Gen AI Applications Architect

Job Description Summary

GE Vernova is accelerating the path to more reliable affordable and sustainable energy while helping customers power economies and deliver electricity that is vital to health safety security and quality of life. Are you excited by the opportunity to electrify and decarbonize the world

We are seeking a highly skilled Senior AI/ML Applications Architect to lead the design development and deployment of advanced machine learning generative AI and agentic AI solutions. This role combines deep technical expertise in AI/ML architecture with technical leadership and requires someone who can drive innovation from concept to production while guiding high-performing project teams.

The role will advise product and engineering teams on architecture and solution approaches for generative AI and agentic AI including the monitoring observability and guardrails required for responsible deployment. The role will also develop proofs of concept and enable production deployment of models across edge and cloud environments including AWS or comparable cloud infrastructure.

The role reports to the Director of Data Analytics and AI Solutions in the Grid Automation CTO organization and collaborates closely with Grid Automation product lines R&D teams product management and other functions to drive efficiency and innovation.

Job Description

Roles and Responsibilities

• Design and architect scalable AI/ML solutions including generative AI and agentic AI applications for grid automation digitalization product-line use cases and business efficiency. Ensure performance across edge and cloud deployment environments.
• Establish architectural standards best practices and technical guidelines for AI/ML development across the CTO organization in collaboration with GE Vernova AI/ML partners.
• Build a strong technical foundation using modular and microservices architectures cloud and edge patterns API-first and privacy-by-design principles containerization orchestration autoscaling infrastructure as code CI/CD data and MLOps pipelines and collaborative experimentation environments.
• Design and deploy solutions on GE GridNode and other edge platforms using container and microservices principles. Develop strategies to optimize model performance in production.
• Advise project and product teams on architecture and solution approaches for generative AI and agentic AI use cases including model selection orchestration patterns and integration strategies.
• Define and implement monitoring observability and guardrails for generative AI and agentic AI solutions including controls for safety security bias hallucination mitigation cost and performance.
• Guide teams in building production-quality systems and reusable frameworks that are scalable reliable and maintainable.
• Collaborate with cross-functional teams to integrate AI/ML capabilities into existing platforms and develop new intelligent product and business-efficiency solutions.
• Monitor advances in AI/ML generative AI agentic AI and energy-system technologies and translate relevant developments into practical recommendations.
• Evaluate AI/ML tools platforms methodologies and vendor solutions for grid-automation challenges and business opportunities. Design and execute proofs of concept to validate feasibility and inform production decisions.

Required Qualifications

• Bachelors degree in Computer Science Electrical Engineering Data Science or a related technical field.
• Minimum of 7 years of hands-on experience in software engineering AI/ML development and/or solution architecture.
• Demonstrated hands-on experience building and architecting generative AI and agentic AI solutions and applications.
• Experience architecting and implementing generative AI and agentic AI solutions on AWS or comparable cloud infrastructure such as Microsoft Azure or Google Cloud Platform.

Desired Characteristics

• Proven expertise with machine learning frameworks such as TensorFlow PyTorch or scikit-learn and with generative AI technologies including large and small language models diffusion models and GANs.
• Experience with agentic AI frameworks and architectures including multi-agent orchestration tool and function calling retrieval-augmented generation agent memory and planning.
• Experience implementing monitoring observability and guardrails for generative AI and agentic AI systems including safety security bias hallucination cost and performance controls.
• Experience applying AI/ML frameworks AI/MLOps and CI/CD across cloud-native and on-premises development and deployment in operational technology or industrial automation environments.
• Experience developing and deploying ML models using cloud MLOps services such as Amazon SageMaker Azure Machine Learning Google Vertex AI Dataiku Cloud or equivalent.
• Hands-on experience developing and testing AI/ML algorithms and experience with grid or physics models using MATLAB PSCAD PSS/E DIgSILENT PowerFactory or equivalent tools.
• Experience with DevOps data pipelines model registries and deployment technologies such as Docker and Kubernetes.
• Experience designing solutions across the complete AI/ML lifecycle: data acquisition data quality and engineering model selection and evaluation tuning testing deployment monitoring maintenance and evolution.
• Strong background in edge computing industrial IoT real-time processing and cloud platforms such as AWS Microsoft Azure or Google Cloud Platform.
• Experience with graph databases SQL and NoSQL databases and Microsoft Access.
• Proficiency in Python and at least one additional language such as C# or C along with experience in scientific programming or simulation tools such as MATLAB or R.
• Experience with time-series analysis signal processing load forecasting or predictive modeling relevant to energy systems and grid operations.
• Proven record of delivering complex AI/ML projects from conception through production deployment.
• Ability to apply research insights to real-world business problems and commercial solutions while balancing innovation implementation constraints security maintainability and business requirements.
• Understanding of industrial IoT edge-computing requirements and real-time data processing in critical-infrastructure environments.

**For candidates applying to a Canadian-based position the pay range for this position is between $126000.00 - 189000.00 CAD Annual. The specific pay offered may be influenced by a variety of factors including the candidates experience education and skill set.

Bonus eligibility: discretionary annual bonus.

This posting is for a new vacancy.

Additional Information

Relocation Assistance Provided: No

#LI-Remote - This is a remote position

Required Experience:

Senior IC