Technical Architect

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 Client 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