Generative AI Lead Requisition ID 35793 Posting Start Date Jul 28, 2026 Posting End Date Sep 26, 2026 Recruiter Abhishek Arora Job Details Area(s) of responsibility

1. Job Title: DataScience GEN AI Lead
Location: Noida/Pune/Bengaluru/Chennai/Mumbai
Experience: 6-8 years
Mode - Hybrid
Role - Fulltime

JOB DESCRIPTION:
The Technical Lead will focus on the development, implementation, and engineering of GenAI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Technical Lead will be responsible for building applications from the ground up, ensuring robust, scalable, and productive solutions.

Required Skills :
1. Python Programming: Deep expertise in Python for building GenAI applications and automation tools.
2. Productionization of GenAI application beyond PoCs Using scale frameworks and tools such as Pylint,Pyrit etc.
3. LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.
4. Large-Scale Data Handling & Architecture:



Design and implement architectures for handling large-scale structured and unstructured data.
5. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
6. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
9. Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development.
10. Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications.
11. Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods.
12. LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.
13. Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.
14. RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.
15. Data Modernization: Expertise in modernizing and transforming data for GenAI applications.
17. API Integration: Experience with REST, SOAP, and other protocols for API integration.

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