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AI Engineer with less than a year in NLP, LLM & RAG Systems
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.Tech (AI & ML) student with experience ranging from training Transformer architectures from scratch to shipping production LLM systems. Currently working across NLP, emotion-aware AI system design, multi-LLM orchestration, and RAG pipelines — the kind of work where architecture decisions actually have consequences.
Dayananda Sagar University
B.Tech · Computer Science (AI & ML)
August 1, 2022 – Present
NEXR Technologies Pvt Ltd
AI/ML Intern
March 1, 2026 – Present
India
NanoGPTX
October 1, 2025 – January 1, 2026
Built a Large Language Model from scratch. Reduced model perplexity from 195 to 10 through dataset scaling, learning rate scheduling, and training pipeline optimization. Implemented a decoder-only Transformer architecture with multi-head self-attention, positional embeddings, layer normalization, and residual connections. Conducted ablation studies across 6 depth configurations to evaluate architecture efficiency and diminishing performance returns.
ALTER
July 1, 2025 – September 1, 2025
Personal AI Persona & Professional Companion. Built a persistent AI alter-ego chatbot for personal portfolio website for professional usecase. Engineered intelligent email capture and real-time notification routing pipelines using Pushover for streamlined communication workflows. Deployed it to HuggingFace spaces and integrated it into my personal portfolio website.
ZeroOne
April 1, 2025 – June 1, 2025
Agentic Startup Validation Engine. Reduced multi-agent execution latency by 60% using asynchronous persona simulations with asyncio.gather. Built a deterministic LangGraph DAG pipeline executing startup validation workflows across Differentiation, Buyer Persona, and Skeptic agents. Improved reliability of LLM-generated insights through anti-hallucination calibration pipelines aligned with benchmark datasets.
Production-Ready RAG API with MLOps Deployment
January 1, 2025 – March 1, 2025
Built an end-to-end RAG pipeline covering document ingestion, embedding generation, semantic retrieval, and LLM response generation. Optimized FAISS and ChromaDB vector retrieval pipelines for low-latency, high-relevance semantic search at scale. Containerized and deployed scalable AI services using Docker, Kubernetes, FastAPI, and REST-based infrastructure.
Cultural Fit Analysis
The candidate's diverse personal projects, ranging from building LLMs from scratch to deploying RAG APIs and agentic systems, indicate a strong passion for AI and a continuous learning mindset. The current internship role aligns well with the target AI Engineer position, demonstrating practical application of skills in a professional setting. The breadth of technologies and concepts covered suggests adaptability and a willingness to explore different facets of AI engineering.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative through personal projects, showcasing a proactive approach to learning and applying advanced AI concepts. The detailed project descriptions suggest good problem-solving skills and an ability to work independently on complex technical challenges. The focus on production-readiness and MLOps indicates an understanding of operational requirements for AI systems.