Senior Generative Ai Enterprise Architect

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 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 DALLE 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