Generative AI Engineer

A Leading Global Consultancy is seeking a highly skilled Generative AI Engineer to join its enterprise analytics practice. In this advanced technical role, you will design and develop enterprise-grade AI/ML and Generative AI platforms using open-source technologies. Furthermore, you will build end-to-end solutions covering data ingestion, retrieval, model serving, and monitoring. Consequently, this position is vital for deploying production-ready platforms that drive intelligent automation for global banking and corporate clients.

The Generative AI Engineer must demonstrate expert programming capabilities in Python infrastructure development and LLM orchestration. Additionally, you will create scalable architectures featuring recursive chunking, metadata tagging, and advanced hybrid semantic search. Therefore, the firm is looking for a platform engineer with hands-on experience reducing hallucinations and building multi-agent workflows. If you want to deploy edge AI modules within an elite MLOps pipeline, this position offers an exceptional step.

Key Responsibilities

• Design and engineer scalable enterprise AI/ML frameworks using modern open-source toolkits.
• Build production-grade Generative AI applications leveraging GPT-4/4o and advanced foundation models.
• Create high-performance REST APIs using FastAPI to implement multi-turn agent workflows.
• Design and optimize complex Retrieval-Augmented Generation (RAG) architectures using LangChain and LangGraph.
• Implement recursive data chunking, structured metadata tagging, and hybrid semantic search techniques.
• Reduce model hallucinations and improve response quality through sophisticated data retrieval strategies.
• Build containerized deployment solutions utilizing Docker inside robust CI/CD and MLOps structures.
• Ensure maximum platform scalability, high availability, security governance, and responsible AI compliance.
• Collaborate with business and analytics teams to develop automated insights and predictive models.
• Integrate intelligent conversational AI modules and multi-agent systems with enterprise core data grids.

Requirements and Qualifications

• B.Tech / B.E. / M.Tech in Computer Science, Software Engineering, or a highly quantitative science discipline.
• 3 – 6 years of successful IT experience, with at least 2 years explicitly focused on GenAI or Data Science projects.
• Expert programming command over Python, SQL database querying, FastAPI platforms, and Docker.
• Hands-on technical mastery of Vector Databases (such as FAISS), Azure AI Search, and RAG orchestration tools.
• Familiarity with predictive analytics, multi-agent framework governance, and enterprise deployment setups.