GenAI Engineer

Key Responsibilities: 3+ years of experience as a NLP and Python developer. Experience with Pandas, NumPy, Scikit, NLP a must have Key fundamentals in object-oriented design, data structures and systems. Ability to integrate multiple data sources into a single system. Familiarity with testing tools. Ability to collaborate on projects and work independently when required. Working knowledge of GitHub and Jira Ability to document requirements and specifications. Develop and maintain advanced Python-based applications in the Generative AI domain, ensuring high performance, reliability, and scalability. Implement and optimize Generative AI models, including GPT, LLAMA, Mistral, FLAN T5 and other cutting-edge AI technologies, to create innovative solutions and knowledge graph. Development of advanced RAG pipelines with proper embeddings, indexing, chunking, reranking, prompts and evaluation Collaborate with cross-functional teams to integrate AI functionalities into broader systems and applications. Utilize AWS/Azure/Databricks GPU machines to manage GPU memory effectively, maximizing performance and efficiency. Stay updated on the latest advancements in Generative AI, Python development practices, and cloud services to continually enhance our AI capabilities. Assist delivery leads in delivering Generative AI solutions to clients in a timely manner, ensuring client satisfaction and project success. Design and develop Agentic AI and Multi-Agent Systems leveraging frameworks such as LangGraph, CrewAI, AutoGen, to enable autonomous reasoning, orchestration, task execution, and enterprise workflow automation. Experience with cloud platforms such as Azure, AWS, and Databricks, along with containerization and orchestration technologies including Docker, Kubernetes, AKS, and EKS, is highly preferred Required Skills and Experience: Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience. 3+ years of experience in data science, building hands-on ML models. Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Knowledge of advanced RAG pipelines with proper embeddings, indexing, chunking, reranking, prompts and evaluation Excellent programming skills in Python. Strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc SQL skills with SQL Server and Spark experience is preferred but not necessary. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment same as above Bachelor's/Master's in Engineering 2-6 years