Director - Data & Analytics with focus on Agentic AI and Generative AI

Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.  

Responsibilities: 

Strategic Leadership 

• Define and execute the long-term roadmap for Agentic AI and GenAI initiatives. 

• Identify and prioritize opportunities where autonomous agents and generative AI can drive business value. 

• Collaborate with executive leadership to align AI strategy with overall business goals. 

Must have Technology & Research Oversight 
 

• Lead architecture and hands-on development of intelligent agent frameworks (e.g., goal-driven, tool-using agents). 

• Oversee the application of LLMs, multimodal models, and fine-tuning strategies for domain-specific use cases. 

• Evaluate and integrate emerging GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.). 

        • Advanced proficiency in Python. 

        • Extensive experience with LLM frameworks (Hugging Face, Transformers, LangChain) and prompt engineering techniques. 

Must have: 

• Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation 

• Expertise in feature engineering, embedding optimization, and dimensionality reduction 

• Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing 

• Experience with RAG systems, vector databases, semantic search implementation and Knowledge graph. 

• Proficiency in LLM optimization techniques including quantization and knowledge distillation 

• Understanding of MLOps practices for model deployment and monitoring 

Team Management & Collaboration 
 

• Build, mentor, and scale a world-class team of AI researchers, ML engineers, and product managers. 

• Foster a strong interdisciplinary culture of innovation and experimentation. 

• Collaborate cross-functionally with data engineering, product, legal, and design teams. 
   

Operational Excellence 

• Oversee data pipelines, model training, inference infrastructure, and model governance. 

• Establish benchmarks and evaluation protocols for agent behavior, safety, and performance. 

• Ensure ethical and responsible AI development practices are followed. 

Good to have Domain/functional knowledge  

• Experience in financial services domain will be a plus.  

• Experience in solving use cases in Asset management, Wealth management or investment banking using AI/ML. 

Mandatory skill sets: 

GenAI/Agentic technologies (e.g., AutoGPT, LangChain, ReAct, DSPy, etc.). 
 

Preferred skill sets: 

• Lang Experience in industries such as finance, consulting 

• Track record of publishing or contributing to open-source AI frameworks. 

• Understanding of regulatory, ethical, and societal implications of autonomous AI system 

Years of experience required: 

14-17 

Education qualification: 

B.Tech / M.Tech / MBA / MCA