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AI Engineer with less than a year in AI/ML & Full-Stack Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Passionate postgraduate in Computer Science with a specialization in Artificial Intelligence, focused on understanding core concepts and applying them to real-world solutions. A collaborative learner with a strong continuous-improvement mindset, especially in AI, machine learning, and deep learning. Committed to staying updated with emerging technologies and contributing effectively to team objectives.
KERALA UNIVERSITY CAMPUS
M.Sc. Computer Science · Computer Science with specialisation in Artificial Intelligence
August 1, 2023 – June 30, 2025
Creative App Lab
Flutter Developer Internship
March 1, 2025 – June 30, 2025
Thiruvananthapuram, Kerala, India
Internship Studio
Artificial Intelligence Internship
April 1, 2024 – June 30, 2024
India
Multi-Agent Intelligent Temporal Query Assistant for Automotive Diagnostics (Hybrid GraphRAG)
February 1, 2025 – July 31, 2025
Built a multi-agent Hybrid GraphRAG assistant that answers natural-language automotive diagnostic queries by combining semantic search with Neo4j graph exploration and temporal reasoning. Developed a Hybrid GraphRAG pipeline integrating Neo4j graph exploration with FAISS-based semantic retrieval. Designed and implemented a multi-agent architecture for query planning, entity matching, graph navigation, and response generation. Modeled automotive diagnostic data in Neo4j, including CAN_ID, Message, Signal, Timestamp, PhysicalValue, and temporal relationships. Processed free-text queries using regex + Sentence Transformers for entity and signal identification. Auto-generated Cypher queries to handle temporal filters, aggregations, value extraction, and relationship patterns. Integrated Gemini API to generate context-aware answers enriched with graph insights. Optimized system performance via schema discovery, temporal-field detection, FAISS vector tuning, and query optimization.
Real-Time Voice Conversational AI Assistant
January 1, 2025 – February 28, 2025
Built a low-latency real-time voice assistant using Groq LLaMA3, LangChain, and Deepgram for fast speech understanding and natural voice responses. Integrated Deepgram Speech-to-Text (STT) and Text-to-Speech (TTS) for real-time speech transcription and natural, human-like audio responses. Connected Groq LLaMA3 through LangChain to deliver ultra-fast, context-aware reasoning, enabling smooth, continuous, and highly responsive conversational interactions. Implemented silence detection and volume-based audio recording for smooth interaction. Added a short-term conversational memory module to maintain context across exchanges, enabling personalized, and context-aware responses. Developed a cross-platform audio pipeline using SoundDevice and Pygame. Built the end-to-end interaction pipeline using Python, handling audio streaming, real-time model responses, and voice output generation.
DevOps specialisation
Unknown
June 1, 2026 – Present
MLOps
Unknown
June 1, 2026 – Present
DataOps specialisation
Unknown
June 1, 2026 – Present
IBM Computer Vision and Image Processing
IBM
June 1, 2026 – Present
Data Science for Engineers
Unknown
June 1, 2026 – Present
Artificial Intelligence Training Certificate
Unknown
June 1, 2026 – Present
Python and Django framework course
Unknown
June 1, 2026 – Present
Data Structures & Algorithms
Unknown
June 1, 2026 – Present
loVent: A Smart IoT System for Automated Air Quality Monitoring and Rule-Based Mitigation System"
IEEE International Conference on Advances in Computing Research on Science, Engineering and Technology (ACROSET 2025)
January 1, 2025 – Present
AutoInsight: Neo4j-Based Multi-Agent GraphRAG Framework for Vehicle Diagnostic Reasoning
Unknown
January 1, 2025 – Present
Qualified UGC-NET PHD Holder
UGC
January 1, 2024 – Present
National Scholarship for Post-Graduate Studies (NSPG)
Ministry of Education, Government of India
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and practical application in cutting-edge AI domains (conversational AI, GraphRAG, multi-agent systems). The diverse set of technologies used (Python, Neo4j, LangChain, Deepgram, various ML libraries) indicates adaptability and a broad technical curiosity. The research experience and certifications further align with a culture of continuous learning and innovation, which is crucial for an AI Engineer role. The internships, while short, show exposure to both AI/ML and full-stack development, suggesting a versatile mindset. The candidate's profile aligns well with a dynamic, research-oriented, and technically challenging environment.
Soft Skills & Operational Fit
The candidate's resume highlights a 'collaborative learner with a strong continuous-improvement mindset' and a commitment to 'staying updated with emerging technologies'. Project descriptions indicate an ability to work on complex, multi-component systems, suggesting good problem-solving and integration skills. The academic achievements and participation in workshops/competitions also point to a proactive and engaged individual. However, without direct interview data, assessing communication clarity in real-time, stress handling, or direct team collaboration effectiveness is limited.