Every learner builds a portfolio of production-grade AI systems throughout the program. From autonomous agents and enterprise RAG pipelines to deployment workflows and observability systems, your work becomes proof of real engineering capability. Along with NVIDIA NCP-AAI certification preparation, learners also receive placement assistance, demo day exposure, and career readiness support designed for the next generation of AI engineering roles.
I'd been a backend developer for nine years — Java, Spring Boot, enterprise APIs. Last year I started seeing job descriptions ask for AI engineering skills I didn't have. I enrolled in the Agentic AI Engineering track half-convinced it was too late. Four weeks later I had a deployed multi-agent system in my portfolio. Within three weeks of graduating, a GCC in Hyderabad reached out through Live Radar. I joined at a 40% salary jump. RED didn't just save my job — it upgraded it.
I finished my B.Tech in 2024 and spent eight months applying to jobs with nothing to show for it. My degree had a two-line mention of machine learning — nothing applied, nothing current. A friend told me about RED's launch batch pricing. I enrolled in AI Ops Engineering. The four weeks were the hardest I've worked in my life. But I graduated with three live projects and a Live Radar profile. A startup in Bengaluru offered me a role before my batch even ended. First salary: ₹11 LPA. I'd been applying for ₹4 LPA roles before.
I'm a VP at a mid-size manufacturing company. For two years I've been sitting in board meetings nodding at AI presentations I didn't fully understand — approving budgets I couldn't evaluate. My team knew it. My vendors definitely knew it. I did the AI for Business Leaders track on evenings, without taking a day off work. By Week 2 I was already asking better questions in vendor calls. My capstone AI strategy document is now our actual company roadmap for FY27. I don't nod anymore. I lead the conversation.
I run a chain of diagnostic labs across Telangana — 14 centres, 200 staff. I did RED's AI for Professionals track because I wanted to use AI in our workflows, not just hear about it at conferences. What I didn't expect was that by Week 3 I'd have three completely new business ideas I'd never considered. AI-assisted radiology report triaging. A WhatsApp-based patient follow-up agent. An internal knowledge system for our lab technicians. I'm building one of them right now with a developer I found through the RED alumni network.
