GEN AI Architect

• Lead solution architecture for new business development and drive end-to-end implementation and deployment.
• Run the solution architecture and proposal defense for reactive and proactive proposal responses for solutions on Generative AI (especially LLMs), Conversational AI & cloud AIaaS.
• Provide leadership for the transformation of customer requirements into visions, strategies, and roadmaps to implement Design Artificial Intelligence solutions and Data Science services platforms at the enterprise scale.
• Independently lead client design workshops and provide tradeoffs and recommendations.
• Develop and implement applications using advanced Generative AI models such as OpenAI GPT, Anthropic Clude, Google Plam2, Meta Llama2, focusing on enhancing developer and business productivity.
• Architect solutions incorporating sophisticated techniques like Retrieval Augmented Generation, In-context Memory, Transformer Architectures, and Hierarchical Models, ensuring optimal model performance and scalability.
• Apply frameworks such as LangChain and Llama Index for efficient indexing, retrieval, and chaining of language models, enhancing the contextual understanding and response generation of applications.
• Integrate multiple components such as data processing, machine learning models, and feedback mechanisms to address architectural challenges and ensure detailed deployment.
• Stay on top of emerging trends, sophisticated patterns, dependencies in data, and advancements in AI architecture, supplying to the refinement and innovation of application development processes.
• Explore and implement inference techniques in generative AI for making predictions or generating new data based on observed input.
• Give to the Cognizant cloud community by developing assets, thought leadership, etc.

Position Qualifications:

• Minimum 15 years of experience with strong expertise in the Data & AI architecture for one of the hyperscaler partners –Azure, AWS, GCP
• Hands-on programming skill in at least one language node.js.
• Expert on Cloud competencies on “Artificial Intelligence” and “Machine Learning” PaaS components:
• Contextual Conversation design– for personalized and humanized interaction with end user for complex business cases:
• Microsoft BOT service
• Google DialogFlow EX,
• Amazon Lex
• Natural Language Processing model - design, training and publishing for multiple languages
• Project experience and/or skills Certification with generative AI:
• Azure Open AI (GPT 3.5/4)
• Google PaLM 2
• AWS Bedrocks
• Emotion and Sentiment Analytics
• Custom Speech model - Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise, and business vocabs.
• Omni-Channel Integration for AI through Direct line
• Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes
• Azure/ AWS/ GCP certifications in Machine Learning & AI:
• Microsoft DP 100, AI 102
• AWS Machine Learning Specialty
• Google Certified Cloud Machine Learning Engineer
• Deeplearning.ai certifications on LLMs, prompt engineering
• Holistic knowledge of Solution Architecture, including “Data Analytics,” “Data Security,” “Dev Ops” & “ML Ops”:
• Web app and services – Microservices, Azure functions, Logic apps, API management
• DevOps CI/CD pipeline on Cloud – “GitHub for Enterprise”
• Ability to compare technologies in any layer objectively with evaluation criteria and considerations.
• Excellent communication skills, preparing PowerPoint presentations, and executive readouts