Generative AI Engineer

Job description

Role – GEN AI Engineer Location – Noida Notice Period – Immediately- 30 days Days Role – GEN AI Developer **Key Responsibilities:** 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. **Fine-Tuning LLMs** : Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases. 9. **LLMOps Implementation** : Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring. 10. **Responsible AI Practices** : Ensure ethical AI practices are embedded in the development process. 11. innovation. **Required Skills** 1. **:Python Programmin** g: 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 Framework** s: 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 7. .Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc 8. .Anti-hallucination and anti-gibberish tools such as Bleu etc 9. **.Front-End Technologie** s: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development 10. **.Cloud Platform** s: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications. **(any two cloud exp.** 11. **)Fine-Tuning Technique** s: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. (any one is fine 12. **)LLMOp** s: Strong knowledge of LLMOps practices for model deployment, monitoring, and management 13. **.Responsible A** I: Expertise in implementing ethical AI practices and ensuring compliance with regulations 14. **.RAG and Modular RA** G: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures 15. **.Data Modernizatio** n: Expertise in modernizing and transforming data for GenAI applications 16. **.OCR and Document Intelligenc** e: Proficiency in OCR and document intelligence using cloud-based tools 17. **.API Integratio** n: Experience with REST, SOAP, and other protocols for API integration 18. **.Data Curatio** n: Expertise in building automated data curation and preprocessing pipelines 19. **.Technical Documentatio** n: Ability to create clear and comprehensive technical documentation 20. **.Collaboration and Communicatio** n: Strong collaboration and communication skills to work effectively with cross-functional teams .