Headline

AI Engineer | LLM & RAG Systems | Python Backend (Django, FastAPI) | Freelance AI Trainer

About

AI Engineer and Python Backend Developer with 2+ years of hands-on experience building production-grade AI, Machine Learning, and Generative AI systems. I specialize in LLMs, RAG pipelines, NLP automation, and scalable backend APIs, delivering solutions actively used by 50K+ users. I have designed and deployed end-to-end AI systems including RAG-powered chatbots, OCR-driven document intelligence pipelines, and ML-powered automation workflows. My work has resulted in 95%+ retrieval accuracy, 40% backend performance improvement, and significant reduction in manual effort across learning and assessment platforms. What I work with it: AI / ML: LLMs, RAG, NLP, Hugging Face, PyTorch, TensorFlow, Semantic Search Backend: Python, Django, FastAPI, REST APIs, Async systems Data Management: PostgreSQL, Redis, Apache Solr, Docker Data Visualization: Matplotlib, Seaborn, Plotly Highlights: Built an RAG-based chatbot improving content retrieval accuracy from 50% → 95%, reducing query load by 60% Developed NLP pipelines processing 10K+ PDFs & videos weekly for AI-driven insights Implemented backend services supporting 50K+ active users, optimizing SQL queries to reduce processing time by 40% Delivered ML & GenAI models for predictive analytics, automation, and decision support Alongside industry work, I am actively involved in freelance teaching and mentoring in AI, Machine Learning, Python, and Backend development. I have previously assisted academic programs and training delivery across multiple institutions, supporting students with LMS platforms, assessments, and applied AI concepts. I thrive in agile, fast-paced environments, collaborating with cross-functional teams to translate business problems into scalable, production-ready AI solutions. Open to opportunities in: Available for freelance training & mentoring in AI/ML and Backend Systems

Location

Madurai South

AI stack

antigravity

claude code

claude

github copilot

Browser Use

Pipedream

Work experience

AI Engineer – LLM & Python Backend Systems at PiRuby, Mar 2025 - Present · 1 yr 8 mos, Bengaluru · Hybrid, • Designed and deployed LLM & RAG-based AI systems using Python, LangChain, FAISS, and Qdrant, improving content retrieval accuracy from 50% to 95% • Built scalable Python backend APIs using Django & FastAPI, supporting 50K+ active users across LMS platforms • Developed NLP and OCR pipelines processing 10K+ PDFs and videos weekly for semantic search and AI insights • Implemented YOLOv8-based proctoring and Deepgram speech analysis, increasing anomaly detection accuracy from 72% to 90% • Optimized PostgreSQL queries and Redis caching, reducing backend processing time by 40% • Containerized AI services using Docker and deployed async systems to achieve sub-second latency • Collaborated with cross-functional product, data, and engineering teams in agile development cycles 🔑 Keywords intentionally repeated: AI Engineer, LLM, RAG, Python, Django, FastAPI, Backend, NLP, PostgreSQL, Docker

Academic Program Coordinator (Teaching) at PiRuby, Nov 2025 - Jan 2026 · 3 mos, Bengaluru · Hybrid, RNS Institute of Technology & SJBIT Group of Institutions – Bengaluru • Facilitated delivery of 4+ technical training programs by coordinating with trainers and ensuring smooth execution of LMS-based online courses • Assisted Python and Cloud (AWS) training programs at RNS Institute of Technology, supporting 200+ students with LMS onboarding, course navigation, assessments, and resolution of technical and subject-related doubts • Handled program coordination activities at SJBIT Group of Institutions, including trainer coordination, scheduling, and student participation tracking • Tracked course progress and engagement metrics for 200+ students, ensuring 95%+ on-time completion of training activities

Trainee Data Scientist at iNetFrame Technologies, Dec 2023 - Mar 2025 · 1 yr 4 mos, Bengaluru · Hybrid, Worked for the client : PiRuby • Designed and deployed LLM & RAG-based AI systems using Python, LangChain, FAISS, and Qdrant, improving content retrieval accuracy from 50% to 95% • Built scalable Python backend APIs using Django & FastAPI, supporting 50K+ active users across LMS platforms • Developed NLP and OCR pipelines processing 10K+ PDFs and videos weekly for semantic search and AI insights • Implemented YOLOv8-based proctoring and Deepgram speech analysis, increasing anomaly detection accuracy from 72% to 90% • Optimized PostgreSQL queries and Redis caching, reducing backend processing time by 40% • Containerized AI services using Docker and deployed async systems to achieve sub-second latency • Collaborated with cross-functional product, data, and engineering teams in agile development cycles • Job Portal Backend: Developed APIs for login/signup, company/job management, candidate matching, and ForgetPassword via Zoho. Implemented resume matching and top-performer selection. Ensured secure, scalable backend. 🔑 Keywords intentionally repeated: AI Engineer, LLM, RAG, Python, Django, FastAPI, Backend, NLP, PostgreSQL, Docker

Data Scientist at iNetFrame Technologies, May 2023 - Nov 2023 · 7 mos, Bengaluru · Hybrid, Worked For the Client: PiRuby • Developed NLP-based chatbots and search systems using Hugging Face, LangChain, and Python • Built FastAPI-based ML APIs for automation and AI-driven workflows • Implemented semantic search pipelines improving response relevance by 80% • Automated LMS data processing and reduced manual operations by 60% • Worked with SQL, REST APIs, and model evaluation pipelines in production environments 🔑 Keywords repeated: Data Science, NLP, Python, Hugging Face, FastAPI, Machine Learning

Data Scientist at PiRuby, Jan 2023 - May 2023 · 5 mos, Bengaluru, Karnataka, India, 1. Developing and Implementing NLP based models for Coreference Resolution. 2. Conducting Data Analysis and Data Preprocessing to support Coreference Resolution models. 3. Building and training Machine Learning models using large scale data sets. 4. Evaluating and optimising the performance of coreference models through experimentation, testing and debugging. 5. Collaborating with cross functional teams to integrate the models into existing systems. 6. Developing with different models to work with Eye Gaze tracking and object tracking and its detection is useful for to monitor the students to proctor for the tests.

Education

Master of Business Administration - MBA, Vellore Institute of Technology

B.Tech (Hons), Electronics and Communication Engineering, Kalasalingam University- Electronics and Communication Engineering Department