Generative AI Developer

Job Title: GEN AI Developer

Location - Noida/HYD/Bengaluru/Pune/Chennai/Mumbai

Experience Required - 4+ years

Key Responsibilities

Application Development: Build GenAI applications from scratch using frameworks like Autogen (applied or acquired), Crew.ai, LangGraph, LlamaIndex, and LangChain.

Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.

Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.

Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.

Fine-tune SLM(Small Language Model) for domain specific data and use cases.

Front-End Integration: Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with GenAI backends.

Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications.

Fine-Tuning LLMs: Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases.

LLMOps Implementation: Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.

Responsible AI Practices: Ensure ethical AI practices are embedded in the development process.

innovation.

Required Skills

Python Programming: Deep expertise in Python for building GenAI applications and automation tools.

Productionization of GenAI application beyond PoCs – Using scale frameworks and tools such as Pylint,Pyrit etc.

LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.

Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.

Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.

Fine-tune SLM(Small Language Model) for domain specific data and use cases.

Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc.

Anti-hallucination and anti-gibberish tools such as Bleu etc.

Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development.

Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications. (any two cloud exp.)

Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. (any one is fine)

LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.

Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.

RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.

Data Modernization: Expertise in modernizing and transforming data for GenAI applications.

OCR and Document Intelligence: Proficiency in OCR and document intelligence using cloud-based tools.

API Integration: Experience with REST, SOAP, and other protocols for API integration.

Data Curation: Expertise in building automated data curation and preprocessing pipelines.

Technical Documentation: Ability to create clear and comprehensive technical documentation.

Collaboration and Communication: Strong collaboration and communication skills to work effectively with cross-functional teams.