Senior Generative Ai Software Architect

Summary The Senior Generative AI Software Architect is a visionary leader responsible for defining and delivering scalable innovative AI solutions using cutting-edge generative AI models This role entails architecting systems that leverage advanced AI to solve complex business problems and enable transformative applications You will support enterprise-scale AI initiatives leveraging Bedrock foundational models Azure OpenAI and Google Gemini The core platform is based on AWS with additional integrations into Azure for specific AI use cases The Senior Architect works closely with product owners data scientists and software development teams to design frameworks deploy models and ensure seamless integration with enterprise systems As a technical authority this role emphasizes system scalability high performance security and ethical considerations You will guide teams in adopting generative AI technologies mentor engineering teams and drive innovation to deliver a competitive edge 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 Architect and oversee the development of robust scalable systems for deploying generative AI models Collaborate with stakeholders to define business requirements and technical specifications for generative AI applications Guide the selection customization and optimization of state-of-the-art generative AI models Develop end-to-end pipelines for model training inference and monitoring in production environments Ensure systems meet high standards for performance scalability and security while adhering to data privacy regulations Lead the implementation of APIs microservices and frameworks to integrate AI models into enterprise solutions Design scalable and efficient architectures for generative AI models applications and workflows Ensure seamless integration of generative AI capabilities into existing systems Provide mentorship to engineering teams fostering expertise in AI and software architecture Design and maintain platforms to handle large-scale solution applications in collaboration with legal and compliance teams Define architectural best practices to mitigate risks associated with Generative AI e g model hallucinations Align AI architecture with organizational goals and contribute to strategic technology roadmaps Document architectural designs workflows and decisions for transparency and scalability Key Technical Skills Strong knowledge of neural network architectures e g CNNs RNNs Transformers Expertise in designing scalable distributed architectures for AI systems Strong experience with cloud computing platforms AWS Azure GCP and containerization Kubernetes Docker Familiarity with large-scale distributed systems and database technologies Experience in creating technical design documents and implementation playbooks for target state AI solutions within cloud environments based on Experience translating business requirements into technical solution designs Thorough understanding of integration platforms and protocols e g REST SOAP HTTP UDP ETC Proficiency in designing RESTful APIs and GraphQL endpoints for AI services Knowledge of API development microservices architecture and DevOps practices Proficiency in MLOps LLMOps and model lifecycle management including CI CD pipelines for training testing and deploying AI models at scale Expertise in prompt engineering and fine-tuning large language models LLMs including techniques like reinforcement learning from human feedback RLHF and parameter-efficient tuning e g LoRA Performance optimization for AI ML workloads including GPU TPU acceleration model quantization pruning and distillation Observability monitoring of AI pipelines encompassing logging tracing and metrics to detect drift anomalies or performance bottlenecks Security Privacy and Compliance knowledge with an understanding of data governance GDPR HIPAA SOC 2 and secure model serving Position Requirements Master s degree or higher in Computer Science Engineering AI or related fields 10 years of experience in software architecture with a focus on AI ML systems Proven track record of designing scalable generative AI use case solutions Exceptional leadership strategic thinking and problem-solving abilities Excellent communication skills for engaging with stakeholders across technical and business domains Must be willing to work out of an office located in Bangalore India Additional Information Relocation Assistance Provided Yes