Senior Generative AI Software Architect

Job Description 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 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 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:

• 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 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