About the Role

Jade Global is seeking an experienced AI/ML Engineer to join our team in Pune. This role focuses on building and deploying cutting-edge Generative AI applications, leveraging large language models (LLMs) and advanced AI frameworks.

Key Responsibilities

• End-to-end development and deployment of LLM-based Generative AI applications.
• Collaborate with a variety of LLMs including OpenAI/Azure OpenAI, Gemini, Claude, LLaMA, and Mistral.
• Design and implement agentic and multi-agent systems using frameworks like MCP and A2A.
• Develop Retrieval-Augmented Generation (RAG) pipelines and document intelligence solutions.
• Utilize modern GenAI frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, and Google ADK.
• Build robust AI backend services using Python with FastAPI and Flask.
• Develop and integrate interactive chat UIs, copilots, and dashboards with AI APIs.
• Productionize, deploy, and monitor AI systems on leading cloud platforms.
• Ensure the performance, security, scalability, and Responsible AI compliance of AI systems.

Required Skills and Qualifications

• Proficiency in Python programming, specifically with FastAPI and Flask.
• Strong foundational knowledge of Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI concepts.
• Hands-on experience with LLMs, embeddings, and prompt engineering techniques.
• Demonstrated experience in designing agentic systems using MCP / A2A.
• Expertise in RAG architectures and experience with various vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma, Milvus).
• Working knowledge of front-end technologies including HTML, CSS, JavaScript, and Streamlit; React experience is preferred.
• Proficiency in API design and integration (REST / WebSockets).
• Strong MLOps experience for deployment on Azure, AWS, or GCP, including Docker, Kubernetes, CI/CD pipelines, and tools like MLflow, Azure ML, SageMaker, or Vertex AI.

Desirable Skills

• Experience with fine-tuning open-source LLMs using techniques like LoRA, PEFT, and the Hugging Face ecosystem.
• Familiarity with autonomous agents and asynchronous workflows.
• Exposure to integrating Robotic Process Automation (RPA) with Agentic AI.
• Understanding of AI governance, monitoring, and security best practices.