Python AI Engineer

Overview

Seeking a proficient Python AI Engineer with over four years of professional experience to join a Forbes Global 2000 investment banking MNC based in Gurugram. This full-time position requires immediate availability and offers a hybrid work model.

Roles and Responsibilities

• Design and develop scalable Artificial Intelligence and Generative AI applications using Python, FastAPI, and RESTful APIs.
• Create and enhance solutions involving Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI technologies.
• Utilize frameworks and APIs such as LangChain, LangGraph, OpenAI, and Hugging Face for AI development.
• Build AI agents, implement tool-calling workflows, and manage multi-agent AI systems.
• Implement embeddings, perform vector and semantic search operations using vector databases like Pinecone and FAISS.
• Architect data pipelines for ingestion, preprocessing, retrieval, and evaluation of AI-related data.
• Integrate AI functionalities with databases, APIs, and enterprise-grade applications.
• Deploy and maintain AI solutions in production environments using Docker containers and cloud infrastructure.
• Enhance application performance, scalability, reliability, and the quality of AI-generated responses.

Essential Qualifications and Skills

• Minimum 4 years of Python programming experience.
• Hands-on expertise with FastAPI or Flask and designing REST APIs.
• In-depth knowledge of Large Language Models, Generative AI, and Retrieval-Augmented Generation techniques.
• Proficiency with LangChain and LangGraph frameworks.
• Experience using OpenAI or comparable LLM APIs.
• Familiarity with vector databases, embeddings, and semantic search technologies.
• Strong background in SQL and database management concepts.
• Practical understanding of version control using Git, containerization with Docker, and Continuous Integration/Continuous Deployment (CI/CD) practices.
• Experience with cloud platforms such as AWS, Azure, or GCP is desirable but not mandatory.

Additional Preferable Skills

• Knowledge of Agentic AI and multi-agent system design.
• Experience with RAG evaluation tools like RAGAS and LangSmith.
• Familiarity with tool or function calling mechanisms such as MCP.
• Competency in machine learning frameworks including PyTorch, TensorFlow, and Scikit-learn.
• Exposure to Kubernetes and cloud-based deployment strategies.

Eligibility

Applications are open to any graduate meeting the above technical qualifications and experience.