AI Infrastructure & RAG Engineering Intern

AI Infrastructure & RAG Engineering Intern **Company:** Autokryx Technologies Private Limited **Product:** INSIDE — The Intelligence Layer for Higher Education **Employment Type:** Internship **Work Mode:** Hybrid **Stipend:** Up to ₹5,000/month, performance-based About the Role We are looking for an **AI Infrastructure & RAG Engineering Intern** to work closely with our engineering team on backend infrastructure, data systems, retrieval-augmented generation, semantic search, and AI-powered applications. This is a hands-on engineering role involving real product infrastructure, databases, APIs, cloud systems, and LLM pipelines. What You’ll Work On * Design, develop, and maintain PostgreSQL databases * Build database synchronization and data ingestion pipelines * Develop REST APIs and backend services * Work with Node.js / TypeScript / Deno * Build and optimize RAG pipelines * Implement embeddings, vector search, and semantic retrieval * Work with **pgvector** and PostgreSQL-based vector infrastructure * Develop prompt engineering and LLM workflows * Build real-time data aggregation and processing systems * Integrate and manage AWS cloud infrastructure * Improve retrieval quality, latency, reliability, and scalability of AI systems * Debug, test, document, and optimize production-oriented systems Required Skills * Strong understanding of PostgreSQL and relational databases * Familiarity with backend development and REST APIs * Working knowledge of Node.js, TypeScript, or Python * Understanding of Git and GitHub * Basic understanding of AI/LLM applications * Understanding of RAG, embeddings, or semantic search * Strong problem-solving and debugging ability Good to Have * Experience with **pgvector** * Experience building RAG applications * AWS experience * Deno experience * Experience with vector databases * Experience with real-time systems / WebSockets * Experience with LLM APIs * Knowledge of data pipelines and asynchronous processing * Understanding of database indexing and query optimization Who Should Apply We are looking for someone who enjoys **building systems** , not just following tutorials. You do not need to know every technology listed above. Strong backend fundamentals combined with genuine hands-on experience in AI/LLM projects are highly valued. Candidates with personal projects, GitHub repositories, deployed applications, or previous experience building RAG/AI systems are encouraged to apply. Stipend **Up to ₹5,000 per month — performance-based.** Performance will be evaluated based on technical contribution, quality of implementation, ownership, consistency, problem-solving, and ability to deliver assigned engineering work. What You’ll Gain * Hands-on experience building AI infrastructure * Practical exposure to RAG and LLM systems * Experience with PostgreSQL, pgvector, APIs, and AWS * Exposure to production-oriented engineering practices * Opportunity to work on a live AI product * Direct collaboration with the core engineering team Application Please apply with your **resume and GitHub/portfolio** . Candidates may be asked to complete a technical assessment or technical discussion as part of the selection process.