You must have 12–13 years of IT experience with 3+ years in GenAI/NLP solution architecture.
Expertise in designing and implementing NLP/LLM pipelines (e.g., summarization, classification, conversational AI).
You should have hands-on experience with Azure OpenAI, Cognitive Services, Azure ML, and agentic AI libraries like LangGraph, LangChain.
You must be skilled in fine-tuning pre-trained LLMs (GPT, LLaMA, BERT) and optimizing models for performance and efficiency.
Knowledge of AI governance, monitoring, and compliance; able to advise clients on NLP/LLM strategies and architectures.
Strong collaboration and communication skills for technical documentation, presentations, and stakeholder engagement.
Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Skills
Data science, AI and ML architecture, GenAI, NLP ,LangGraph, LangChain ,Azure foundry ,Azure OpenAI and GPT
Your Team
You will work with a top-tier organization that's been in the game for 50 years, partnering with some of the world's biggest businesses. As India's largest multinational business group, they boast a workforce of over 500,000 highly skilled consultants spread across 46+ countries. Beyond that, they're at the forefront of the financial markets and data industry, delivering exceptional services in Data & Analytics, Capital Markets, and Post Trade. Their commitment to excellence reverberates in everything they do.
Your Job
You will design, implement, and optimize Generative AI and NLP solutions for complex business use cases using LLMs and agentic AI systems.
You will define and own the end-to-end architecture for AI systems leveraging Azure AI services (Azure OpenAI, Cognitive Services, Azure ML) and agentic libraries such as LangGraph and LangChain.
You should develop NLP/LLM pipelines for information extraction, summarization, classification, conversational AI, and other advanced tasks.
Ability to fine-tune and customize pre-trained models (GPT, LLaMA, BERT) to meet client-specific requirements.
You will evaluate, compare, and select LLM approaches for performance, accuracy, and efficiency, ensuring alignment with AI governance and regulatory standards.
collaborate with data scientists, engineers, and product stakeholders to align technical solutions with business objectives.
create documentation, presentations, and technical reports for both technical and non-technical audiences.
Updated on NLP/LLM advancements and provide thought leadership, contributing to knowledge sharing and internal capability building.
