Prompt Engineering
"Architecting next-generation RAG pipelines and sophisticated prompt orchestration for enterprise-grade conversational agents."
Commitment Period
6 Months
Work Protocol
Hybrid
Geo Location
Bangalore, India / Remote
Architectural Roadmap
A high-performance Document Q&A Chatbot capable of processing multi-format enterprise data (PDF, Markdown, SQL) using a RAG architecture. The system will feature semantic search, metadata filtering, and a React-based frontend for real-time interaction.
Advanced Prompt Engineering (Few-shot
Chain-of-Thought
ReAct)
Vector Database Indexing & Query Optimization
LLM Evaluation Frameworks (RAGAS
TruLens)
Deployment of scalable AI APIs via FastAPI and AWS ECS
Handling Hallucinations and Implementing Guardrails
Personnel Eligibility
Final year CS/AI students or recent graduates with strong Python proficiency and a foundational understanding of NLP/Transformer architectures. Prior experience with vector databases or LLM APIs is highly preferred.
Compensation Matrix
Industrial Standard
Competitive monthly stipend based on technical assessment + performance-based bonuses upon successful project deployment.
Personnel Guide
Raghavendra N
Founder & CEO
"Raghavendra N is the visionary architect behind CodeOrigin.ai, specializing in the intersection of Generative AI and enterprise-scale infrastructure. With over 15 years of experience leading digital transformation initiatives for global enterprises, he has a proven track record of deploying robust LLM frameworks and high-concurrency distributed systems. His expertise spans the full lifecycle of AI integration—from strategic feasibility studies to production-grade RAG (Retrieval-Augmented Generation) architectures using AWS and Azure. Under his leadership, CodeOrigin.ai delivers high-performance, secure, and scalable technology solutions that drive measurable ROI through intelligent data orchestration and cloud-native engineering."
Initialize Your
Professional Track
Elite mentorship and production-grade system development orchestrated in every technical node.