A live immersion program for software engineers who want to break through, earn more, and work at the frontier of AI.
Your skills are solid but your profile looks the same as everyone else applying for the same roles.
AI is moving fast. You have picked up tools here and there but you do not know how to build with AI end to end.
You hit a ceiling. The next level of work and pay exists but no one is showing you a clear path to get there.
You have done courses. They gave you knowledge. Not output. Not proof of work. Not a new job offer.
RAD Pioneer is run by engineers who build AI-native products for global companies every day. You do not watch videos. You work on real problems alongside real practitioners, every week.
You work on actual industry backlogs, not toy projects. Your output is real and your portfolio proves it.
Every session is led by Fleet Studio engineers who are actively shipping AI products for global clients.
You leave with a production-grade AI application, a strong portfolio, and a score that recruiters can trust.
Priority access to hiring partners, fast-tracked interviews, and one-on-one career coaching are part of the program.
Each week: 4 hours of live sessions + 4 hours of capstone work on real problems.
| Weeks | Track | What you learn and build |
|---|---|---|
| 1–2 | Foundations | Neural networks, transformer architecture, how AI models work, ecosystem overview |
| 3–4 | Foundations | LLMs deep dive: fine-tuning, RAG, embeddings, vector databases, prompt engineering |
| 5–6 | Foundations | Hands-on model projects: RAG pipelines, embedding search, model evaluation with expert reviews |
| 7–8 | RAD MCP | MCP architecture, building MCP servers, connecting AI to real-world tools |
| 9–11 | RAD MCP | AI agent design, advanced prompting, orchestration, guided capstone sprints |
| 12–13 | AI-Native SWE | AI-native architecture, LLM-integrated systems, quality and security |
| 14–15 | AI-Native SWE | Unguided capstone sprint: architect and ship a complete AI-native application |
| 16 | AI-Native SWE | Expert reviews, final showcase, portfolio completion, job placement starts |
Years of experience but not landing the roles or CTCs that match your ability.
A solid software background and want to move into AI engineering without going back to school.
You use AI tools daily but do not yet build AI systems from scratch with confidence.
Already strong, want to become the most valuable person in any engineering room.
Build features in hours that used to take days. AI becomes your force multiplier, not your assistant.
The program pays for itself within the first year. Most fellows see the return within 16 weeks.
AI-native engineers command a different pay bracket. RAD Fellows move into that bracket.
Every RAD Fellow gets direct access to hiring partners, placement support, and fast-tracked interviews.
Every session is led by Fleet Studio practitioners who build AI-native products for enterprise and global clients every day. Theory stays out. Real work comes in.
15+ years building real products for Fortune 500 companies. The curriculum is what the team actually does at work.
Every session is live. You build alongside your instructors, ask questions in real time, and get reviewed by them.
One-on-one feedback from industry leads. Your code, your architecture, your thinking is reviewed every week.
You work with a small batch of serious engineers. The connections you make here last past the program.
16 weeks. Real work. Real proof. A new career bracket waiting on the other side.
Apply Nowacademy@fleetstudio.com | +91 99448 80262 | academy.fleetstudio.com