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AI Engineer with less than a year in Machine Learning & RAG Architectures
Third-year B.E. candidate specialising in Artificial Intelligence and Machine Learning at Osmania University, with demonstrated expertise in large language model integration, retrieval-augmented generation (RAG) architectures, and multimodal system design. Holds two concurrent industry internships (Data Science at The Skybrisk; Web Development at Unify Labs) and has won the 'Best Hack on Al Track' award at HackPrix, a 48-hour national hackathon supported by AWS and Devfolio. Proficient in architecting end-to-end Al pipelines from NLP preprocessing and deep learning inference to full-stack deployment with a focus on socially impactful applications for Indic-language communities. Seeks to contribute to and deepen expertise in applied machine learning and intelligent systems.
Osmania University
Bachelor of Engineering · Artificial Intelligence & Machine Learning
August 1, 2023 – June 30, 2027
The Skybrisk (theskybrisk.com)
Data Science Intern
February 1, 2026 – May 31, 2026
India
Unify Labs
Web Development Intern
January 1, 2026 – March 1, 2026
India
Blogify & QR Review System - Full-Stack Secure Content Platform
June 5, 2026 – Present
Engineered a security-first full-stack platform with TOTP/OTP multi-factor authentication (HMAC-SHA1), UUID v4 session-bound anti-replay QR tokens, and parameterised SQL injection defences; persistence layer on Supabase (PostgreSQL) with row-level security (RLS) policies and PgBouncer connection pooling for horizontal scalability. Integrated Three.js WebGL 3D interactive UI components with progressive enhancement fallbacks for non-GPU contexts; designed normalised ER schemas with composite indexing on high-cardinality query paths and implemented automated OTP-gated write-operation controls.
KrishAI - Multimodal Agricultural Diagnostic System
June 5, 2026 – Present
Engineered a voice-first NLP pipeline optimised for low-resource regional dialects (Telugu, Hindi, Marathi), incorporating phoneme-level preprocessing, dialect-adaptive tokenisation, and transformer-based intent classification to enable field-level usability without literacy prerequisites, targeting sub-3-second inference latency on low-specification Android devices. Architected a multimodal crop health diagnostic engine fusing CNN-based leaf image analysis with structured agronomic metadata (soil NPK profiles, rainfall indices, pest calendars) to generate probabilistic disease classifications; implemented context-aware dialogue management with RAG-based context injection for coherent multi-turn conversations.
SerenAlve - Digital Mental Health Monitoring System
June 5, 2026 – Present
Architected a React/Node.js/Supabase digital health platform with HIPAA-aligned data minimisation and end-to-end encryption; implemented a fine-tuned BERT-variant sentiment analysis layer classifying user text across emotional valence axes (positive, neutral, distressed, crisis-indicative), producing continuous distress-severity scores per session. Engineered a longitudinal trend analysis subsystem applying windowed time-series modelling over distress scores; statistically significant deterioration trajectories trigger configurable escalation notifications, with strict architectural separation between ML inference pipelines and PII storage.
Cognix - Agentic AI Educational Assistant with RAG Architecture
June 5, 2026 – Present
Architected a multi-agent autonomous workflow orchestrated via n8n (event-driven microservices), wherein specialised agents handle query decomposition, FAISS vector-indexed knowledge retrieval, Gemini API-powered answer synthesis, and citation verification as decoupled pipelines - measurably reducing hallucination rates relative to zero-shot prompting baselines. Implemented real-time educational data ingestion with automatic vector store re-indexing for response currency without model retraining; designed chain-of-thought prompt engineering with confidence-score thresholding to enforce structured, auditable reasoning traces across all agent interactions.
Cultural Fit Analysis
The candidate's diverse project portfolio, including academic and personal projects, showcases a broad interest in AI/ML applications, from agricultural diagnostics to mental health monitoring and educational assistants. Their focus on 'AI for Bharat' and low-resource languages indicates a strong alignment with impactful, community-driven initiatives. Active participation in GDG events and continuous self-directed study demonstrate a proactive and collaborative learning mindset, which is a good cultural fit for innovation-driven teams. The candidate's target role as an AI Engineer aligns well with their demonstrated skills and interests.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative, a proactive learning attitude, and a commitment to socially impactful AI solutions. Their participation in hackathons and community events suggests good collaboration potential and ability to perform under pressure. The detailed project descriptions indicate strong problem-solving skills and an ability to articulate complex technical concepts. However, as an early-career candidate, direct experience in a senior operational role is limited.