**JD / Skillset** :- **Key Responsibilities :-** - Develop end-to-end scalable, optimized enterprise AI solutions. - Engage in prompt engineering and fine-tuning of AI/ML models, including Generative AI (GenAI) and Large Language Models (LLMs), as well as building and managing multi-agent systems. - Implement practical hands-on fine-tuning, transfer learning, and optimization of Transformer architecture-based deep learning models. **Technical Skills** :- - Proficient in Agentic AI, GenAI, and LLM technologies, with experience in NLP tools such as Word2Vec, NLTK, SpaCy, BERT, GloVe, Autogen, Semantic Kernel, Lang chain, and Langraph. - Hands on development experience with development of AI agents. - Familiarity with either of cloud platforms like Azure, AWS or Google Cloud - Strong programming skills in Python, with experience in frameworks such as Flask for lightweight applications and FastAPI for API development. - Proficient in using Docker for container deployment and deploying ML models on Kubernetes clusters. - Experience with NoSQL, SQL, and vector databases. - Strong understanding of statistical methods and experimental design. - Familiarity with MLOps practices for continuous integration and continuous deployment (CI/CD) in machine learning. - Experience in prompt fine tuning and performance optimization - Experience using Python Memory management tools like Scalene or Filprofiler or similar - Experience in any of the Frameworks like Langchain, Langraph etc. - Familiarity of having worked on packages such as Python-pptx, pymupdf to read PPTX or pdf documents. This has to be complimented with hands-on experience integrating OpenAI's GPT models with such Python applications.