Job Description

Area(s) of responsibility

1. Application Development Build GenAI applications from scratch using frameworks like Autogen (applied or acquired), Crew.ai, LangGraph, LlamaIndex, and LangChain.
2. Python Programming Develop high-quality, efficient, and maintainable Python code for GenAI solutions.
3. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
4. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
5. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
6. Front-End Integration Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with GenAI backends.
7. Data Modernization and Transformation Design and implement data modernization and transformation pipelines to support GenAI applications.
8. OCR and Document Intelligence Develop solutions for Optical Character Recognition (OCR) and document intelligence using cloud-based tools.
9. API Integration Use REST, SOAP, and other protocols to integrate APIs for data ingestion, processing, and output delivery.
10. Cloud Platform Expertise Leverage Azure, GCP, and AWS for deploying and managing GenAI applications.
11. Fine-Tuning LLMs Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases.
12. LLMOps Implementation Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.
13. Responsible AI Practices Ensure ethical AI practices are embedded in the development process.
14. RAG and Modular RAG Implement Retrieval-Augmented Generation (RAG) and Modular RAG architectures for enhanced model performance.
15. Data Curation Automation Build tools and pipelines for automated data curation and preprocessing.
16. Technical Documentation Create detailed technical documentation for developed applications and processes.
17. Collaboration Work closely with cross-functional teams, including data scientists, engineers, and product managers, to deliver high-impact solutions.

Mentorship Guide and mentor junior developers, fostering a culture of technical excellence and innovation