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Job Description Summary

The Senior Generative AI Enterprise Architect is a strategic leader responsible

for defining and implementing enterprise-wide strategies to harness the power of

generative AI technologies. This role involves designing and overseeing the

integration of AI solutions into core business processes and IT ecosystems to

drive innovation and deliver transformative results.

The Senior Architect works with C-level executives, business leaders, and

technical teams to align AI initiatives with long-term organizational goals. With

deep expertise in enterprise architecture and generative AI, this role focuses on

creating scalable, secure, and ethically sound systems that deliver measurable

business value. As a thought leader, you will shape the future of AI adoption

within the organization and guide teams toward realizing its full potential.

As a GE Vernova accelerator, GE Vernova Advanced Research is driving

strategy and leading research & development efforts to execute on the

business’s mission to help power the energy transition. We forge the

collaborations and help invent the technologies required to electrify and

decarbonize for a zero-carbon future.

Representing virtually every major scientific and engineering discipline, our

researchers are collaborating with GE Vernova’s businesses, the U.S.

government, and more than 420 entities at the forefront of technology to execute

on 150+ energy-focused projects. Collectively, these research programs and

initiatives aim to solve near term technical challenges, deliver next generation

product advances, and drive long term breakthrough innovation to enable more

affordable, reliable, sustainable, and secure energy.

Job Description

Roles & Responsibilities:

+ Coordinate Tech Council, ensuring that our teams are driving the principles of re-use, scalability, and maintainability as we design and deploy GenAI solutions.

+ Act as the primary liaison with the Chief Information Security Officer (CISO) and Chief Technology Officer (CTO) teams to align security and technology strategies across the organizations.

+ Design and implement scalable, secure, and robust enterprise architectures for generative AI systems that integrate with enterprise IT ecosystems.

+ Work with business and IT stakeholders to define and execute a comprehensive generative AI strategy that aligns with organizational goals.

+ Design and maintain an enterprise AI architecture framework to support scalable, efficient, and secure AI solutions.

+ Collaborate with business leaders to identify high-impact use cases for generative AI technologies.

+ Lead the integration of generative AI systems into enterprise IT infrastructure and workflows. Establish architectural blueprints and best practices for deploying GenAI solutions across various business domains.

+ Guide teams in optimizing AI models for performance and cost, focusing on inference speed and resource efficiency.

+ Oversee the delivery and monitoring of AI systems to ensure they meet operational and performance benchmarks.

+ Partner with stakeholders across the enterprise to create AI-driven solutions that deliver measurable ROIs.

+ Operationalize and enforce organizational AI governance frameworks to ensure ethical, secure, and compliant use of Generative AI.

+ Evaluate and recommend third-party tools, platforms, and partnerships for Generative AI initiatives.

+ Manage relationships with vendors, ensuring alignment with enterprise requirements and scalability.

+ Advocate for innovation and foster a culture of AI adoption across the organization.

+ Stay updated on emerging trends in Generative AI to guide and maintain a roadmap for generative AI projects, ensuring scalability and innovation.

Key Technical Skills:

+ Proficiency with AI/ML frameworks such as TensorFlow, PyTorch, etc. Advanced knowledge of generative AI platforms (e.g., GPT, DALL·E, Stable Diffusion) and frameworks.

+ Deep understanding of Generative AI models (e.g., Transformers, Large Language Models (LLMs) like GPT, Claude, Llama, etc.)

+ Expertise in enterprise architecture methodologies (e.g., TOGAF, Zachman) and IT systems design.

+ Familiarity with Natural Language Processing (NLP), Computer Vision, and Multimodal AI systems.

+ Understanding of GPU/TPU-based acceleration and optimization techniques.

+ Familiarity with MLOps workflows, including CI/CD pipelines for AI systems.

+ Expertise in designing scalable data pipelines for training large AI models.

+ Strong knowledge of vector databases and embedding search tools (e.g., PG Vector, Amazon Titan, Azure Doc intelligence etc.).

+ Familiarity with cloud-based AI/ML services (e.g., AWS Sagemaker, Azure ML, Google Vertex AI) and AI orchestration tools.

+ Strong experience with cloud platforms, data lakes, and enterprise data management systems.

+ Ability to design scalable, modular, and secure AI architectures that integrate with enterprise IT ecosystems.

+ Knowledge of APIs, microservices, and middleware to enable seamless GenAI application deployment.

+ Deep understanding of AI governance, security, and compliance. Strong understanding of domain-specific applications for generative AI (e.g., content generation, chatbots, digital twins, design automation).

+ Proficiency in integrating AI models into enterprise workflows and IT ecosystems.

+ Proficiency in collaborating with cross-functional teams, including data scientists, ML engineers, and business stakeholders.

Position Requirements:

+ Master’s degree or higher in Computer Science, Business Administration, or related fields (Ph.D. preferred).

+ 12+ years of experience in enterprise architecture and AI leadership roles.

+ Demonstrated success in leading AI initiatives and delivering large-scale solutions.

+ Exceptional strategic thinking, analytical, and communication skills.

+ Proven experience as an enterprise architect for a Global Organization

+ Must be willing to work out of an office located in Bangalore, India.

Additional Information

**Relocation Assistance Provided:** Yes

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.