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AI Engineer with less than a year in NLP & Automation
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Anant Mehrotra is an aspiring AI Engineer with a strong foundation in NLP, machine learning, and automation. With 0.9 years of experience as a Chatbot Developer Intern and Technology Consultant Intern, he has developed interactive AI assistants, automated testing workflows, and implemented sentiment analysis pipelines. His project work showcases expertise in RAG systems, face anonymization, and email classification, demonstrating a robust skill set in Python, LangChain, FastAPI, and various AI/ML frameworks.
SRM Institute of Science and Technology
B.Tech · Computer Science and Engineering
August 1, 2021 – June 30, 2025
Amplify.ai
Chatbot Developer Intern
November 1, 2025 – January 31, 2026
India
EY Global Delivery Services (GDS)
Technology Consultant Intern
March 1, 2025 – August 31, 2025
Chennai, Tamil Nadu, India
DocuMind - Interactive PDF Assistant
June 26, 2026 – Present
• Engineered a production-style RAG pipeline using LangChain and FAISS, ingesting multi-page PDFs into semantic vector embeddings and delivering context-aware Q&A with sub-3-second retrieval latency across 50+ page corpora. • Built an end-to-end LLM application with a Streamlit interface, reducing manual document review effort by an estimated 60% in simulated user testing.
View ProjectAutoTriage - Email Classifier
June 26, 2026 – Present
• Developed a multi-class NLP email classification system using TF-IDF vectorization and supervised learning, achieving 92% accuracy across 5 categories on a 10,000+ email dataset. • Built a complete ML pipeline covering text preprocessing, feature extraction, cross-validation, and evaluation automating email routing and reducing manual triaging effort by an estimated 70%.
View ProjectFace Anonymizer
June 26, 2026 – Present
• Implemented an automated face detection and anonymization system using MTCNN deep learning model, achieving 90%+ detection accuracy across varied lighting conditions and multi-face frames with sub-second per-frame latency. • Architected a FastAPI backend with async job handling to decouple inference from delivery, enabling concurrent image and video processing without blocking the Next.js frontend.
View ProjectCultural Fit Analysis
The candidate's project diversity, ranging from NLP email classification to face anonymization and RAG pipelines, indicates a broad interest in AI/ML applications. Their internship experiences, though not directly in AI engineering, show adaptability and exposure to different technical environments (chatbot development, QA automation). The focus on practical, impactful projects aligns with a results-driven culture. However, as an entry-level candidate, their direct experience in a dedicated AI engineering team is limited, which might require a period of adjustment to a senior AI engineering culture.
Soft Skills & Operational Fit
The candidate demonstrates an ability to work in Agile environments and collaborate cross-functionally, as evidenced by their internship at EY GDS. Their project descriptions highlight problem-solving and efficiency improvement, suggesting a results-oriented approach. The experience with automating workflows and reducing manual effort indicates a proactive mindset. However, the candidate's experience level is entry-level, which might require more guidance in a senior role.