Job Summary We are seeking a highly skilled Agentic AI Engineer / Data Scientist to design, develop, and deploy advanced AI-driven systems capable of autonomous reasoning, decision-making, and workflow orchestration. The ideal candidate will have strong expertise in Generative AI, LLMs, AI agents, machine learning, and data science , along with hands-on experience building scalable AI applications in cloud environments. This role involves developing intelligent AI agents, integrating large language models, building ML pipelines, and collaborating with cross-functional teams to deliver innovative AI solutions for enterprise applications. Key Responsibilities Design and develop Agentic AI systems using LLMs, autonomous agents, and multi-agent frameworks Build and deploy AI/ML models for prediction, automation, and intelligent decision-making Develop AI workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel Fine-tune and optimize LLMs including GPT, Llama, Claude, Gemini, or open-source models Create scalable data pipelines for structured and unstructured data processing Implement Retrieval-Augmented Generation (RAG) architectures and vector databases Work with cloud platforms such as AWS, Azure, or GCP for AI deployment and MLOps Collaborate with business stakeholders, product teams, and engineers to define AI use cases Develop APIs and integrate AI solutions into enterprise applications Monitor model performance, accuracy, and scalability in production environments Ensure AI solutions comply with security, governance, and responsible AI standards Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field 5+ years of experience in AI/ML engineering or data science Strong programming skills in Python Hands-on experience with machine learning and deep learning frameworks such as TensorFlow or PyTorch Experience with Generative AI and Large Language Models (LLMs) Expertise in prompt engineering, RAG, embeddings, and vector databases Knowledge of AI agent frameworks like LangChain, CrewAI, AutoGen, or LangGraph Experience with SQL, NoSQL, and big data technologies Familiarity with Docker, Kubernetes, CI/CD, and MLOps practices Experience with cloud AI services on AWS, Azure, or GCP Preferred Qualifications Experience with multi-agent AI systems and autonomous workflows Knowledge of NLP, Computer Vision, or Reinforcement Learning Experience with AI observability and evaluation frameworks Exposure to enterprise AI governance and AI security practices Certifications in Cloud AI or Machine Learning are a plus