Job Description :

Role & responsibilities :

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines.

- Design effective prompt engineering strategies and evaluate model performance.

- Fine-tune or adapt foundation models where appropriate.

- Implement guardrails, evaluation frameworks, and monitoring for GenAI applications.

- Collaborate with Data Science teams to integrate predictive models with GenAI solutions.

- Perform exploratory data analysis and feature engineering to support AI initiatives.

- Evaluate AI models using appropriate performance metrics and business KPIs.

- Design, develop, and deploy GenAI-powered applications for business functions including customer service, underwriting, collections, operations, sales and internal productivity.

- Build conversational AI solutions, copilots, intelligent assistants, document intelligence and workflow automation using Large Language Models.

- Develop scalable AI workflows leveraging APIs and open-source GenAI frameworks.

- Ensure adherence to organizational AI governance, data privacy, security and responsible AI principles.

- Support documentation, testing and model validation processes.

- Stay current with advancements in LLMs, AI agents, multimodal AI and emerging GenAI technologies.

- Evaluate new tools, frameworks and models for potential enterprise adoption.

- Contribute to AI best practices, reusable components and knowledge-sharing within the Analytics function.

Preferred candidate profile :

- Experience Required : Minimum 3+ years or similar.

- NBFC, Banking, FinTech background preferred.

- B.Tech in CS/IT or similar.

- At least 1-2 years of hands-on experience building Generative AI or LLM-based applications.

- Experience in BFSI, NBFC, FinTech or Digital Financial Services is preferred but not mandatory.

- Demonstrated experience in taking AI solutions from proof-of-concept to production is desirable.