What’s currently lacking in India’s AI hiring market is not interest but production depth. A study by Scaler and CyberMedia Research (CMR) surveyed 400 experienced engineers and tech recruiters and found a significant confidence-capability gap. 89% of engineers believed they were AI-ready, yet only 19% were engaged in developing AI/ML systems.Diving into the confidence-capability gapEmployers have moved past AI experimentation, and now they seek candidates who can build robust systems. Recent trends highlight the confidence-capability gap, a shortage of deployment-ready talent, and a demand for agentic AI skills that outstrips supply.The market is rewarding engineers who can make sense of latency, observability, evaluation, orchestration, governance and system reliability. It is here that the difference between GenAI and Agentic AI or RAG engineering becomes vital. GenAI dived into foundation models for content creation, chat style workflows whereas RAG and agentic systems need the architecture around the model: retrieval, memory, tool access, routing, control flow and safeguards.It is here that most teams might hit a wall. A prototype can reach the demo round, but production systems require accuracy checks, source grounding, cost control, tool-failure handling, and more.iHUB DivyaSampark at IIT Roorkee is launching the Batch 1 of the Post Graduate Certificate in Agentic and RAG systems for AI Engineering as a solution to fill this gap.It has been built as a six-month live online programme designed for software engineers, data and AI professionals, tech leads, architects and product managers, who want to build production-ready AI systems.The programme utilises live sessions run by programme leaders. It also incorporates virtual labs, hands-on projects, and a capstone to enable participants to learn how to build RAG applications, autonomous agents, fine-tuned models, and deployable AI systems. Participants also get to attend masterclasses from IIT Faculty.What the programme coversThe Post Graduate Certificate in Agentic and RAG systems for AI Engineering revolves around production engineering: Hybrid retrieval and reranking, failure-mode-aware agent design, fine-tuning with LoRA/QLoRA, and deployment with live observability. It covers Model Context Protocol (MCP), LangGraph, CrewAI, vector databases (Qdrant, FAISS, Chroma), retrieval evaluation and production monitoring. Some of the pillars of the curriculum include AI Engineering Foundations, Enterprise RAG and Retrieval Infrastructure, Model Adaptation and Fine-Tuning etc.What makes this programme tickOne of the appealing aspects about this programme is that it is delivered online, and is scheduled to seamlessly find its place in a working professional’s week without the need for taking a career break.Once the participant completes this programme and meet all the requirements, they will receive a valuable certificate, which is issued by iHUB DivyaSampark, IIT Roorkee, a Government of India DST/NM-ICPS initiative, and carries the IIT Roorkee institutional identity.The positioning of this programme showcases where the industry is moving. Employers seek professionals who can go beyond model prompts and into system design, integration, and governance, especially in roles where AI works with enterprise data and external tools.The relevancy of this programme lies in its narrower focus on the engineering layer between a model and working product, a point where RAG and agentic systems show up. Professionals might be working in software, analytics or data roles but this layer is where they get practical training from the learnings from this programme.Key programme details

Retrieval-Augmented Generation (RAG) and Agentic AI engineering have transformed into core pillars of new-age software development. Several sectors are actively expanding intelligent systems that need specialised skills to build, secure and sustain. The Post Graduate Certificate in Agentic and RAG systems for AI Engineering has been devised to empower professionals with a thorough understanding of agentic systems, and to help them focus on practical applications. This programme seeks to cultivate skilled experts who can be at the forefront of innovation and contribute to the landscape of AI engineering.Disclaimer: This article has been produced on behalf of Emeritus by Times Internet’s Spotlight team.