Job Description:

Strong and proven ability to identify and categorize use cases suitable for Generative AI usage and implementation. This is a key ask.

•Responsible for reactive and proactive proposals responses for solutions involving Generative AI (specially LLMs), Conversational AI & cloud AIaaS.

•Provide leadership for the transformation of customer requirements into visions, strategies, and roadmaps to implement Design AI enabled solutions, Data Science services platform at enterprise scale.

•Strong expertise in the Data & AI architecture for one of the Cloudpartners –Azure, AWS, GCP

•Develop and implement applications incorporating Generative AI models such as GPT, Anthropic Claude,, Google Palm, Meta Llama, focusing on enhancing developer and business productivity.

•Knowledge of MLOPS will be beneficial.

•Architect solutions incorporating Retrieval Augmented Generation, In-context Memory, Transformer Architectures, and Hierarchical Models, ensuring optimal model performance and scalability.

•Apply middleware 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 flawless deployment.

•Keep abreast 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.

Qualifications:

Hands-on programming skill on at least one language node.js/Java/Python

Strong hands-on capabilities on “Artificial Intelligence” and “Machine Learning” PaaS components such as:

•Contextual Conversation design– for personalized and humanized interaction with end user for complex business cases

•Microsoft BOT service, Google DialogFlow EX, Amazon Lex

•NLP model - design, training and publishing for multiple languages

•Project experience and/or skills Certification with generative AI including: Azure Open AI (GPT 3.5/4) , Google PaLM 2 and AWS Bedrock

•Custom Speech model - Speech-to-text and Voice synthesis calibrated for language, accent, pitch, tone, noise and business vocabs.

Standard Architectural Practices As Below:

•Omni-Channel Integration for AI. MLOPS knowledge.

•Deployment and publish for AI and ML services with ACR, ACI, Docker, Azure Kubernetes

•Azure/ AWS/ GCP certifications, AWS Machine Learning Specialty, Google Certified Cloud Engineer and Deeplearning.ai certifications on LLMs, prompt engineering

•Web app and services – Micro services, Azure functions, Logic apps, API management

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