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Full Stack Engineer with 1+ years in Blockchain & AI
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Assessing your cultural and operational fit
Full Stack Developer with 1 year of experience in building AI-powered platforms and secure blockchain solutions. Proficient in React, Node.js, Solidity, Python, and cloud technologies. Successfully developed a Sanskrit pronunciation training platform leveraging AI, simulated cross-chain bridge attacks, and implemented a secure e-voting system using blockchain.
Amrita School of Engineering
B.Tech · Electronics and Computer Engineering
August 1, 2022 – June 30, 2026
Valaxia LLP
Full Stack Developer
December 1, 2025 – Present
India
Dehix
Blockchain Developer
August 1, 2025 – December 1, 2025
India
SanskritAI - AI-Based Sanskrit Pronunciation Training Platform
January 1, 2026 – June 1, 2026
• Built a full-stack Sanskrit pronunciation training platform using React, Node.js and speech inference APIs. • Implemented speech analysis pipeline using Wav2Vec2 XLS-R-300M extracting phoneme-level acoustic logits. • Designed alignment-free mispronunciation detection combining GOP scoring, logit margin and variance. • Achieved ROC-AUC 0.94 across 1500+ synthetic pronunciation samples. • Impact: Sanskrit is one of the most ancient languages but is gradually disappearing as fewer people learn or speak it. This platform makes pronunciation learning accessible through AI-based feedback so learners worldwide can adopt and preserve the language.
Phantom-Read Cross-Chain Bridge Attack Simulation
January 1, 2025 – December 1, 2025
• Designed a cross-chain bridge simulation using 3 Anvil blockchain nodes representing source, forked and destination chains. • Implemented Solidity bridge contracts (120+ LOC) with lock and release mechanisms simulating asset transfers. • Built a malicious relayer using Node.js and Ethers.js that reads events from forked chains. • Developed detection scripts verifying transaction and block hash consistency across canonical and forked chains. • Impact: Demonstrates how relayer-based bridges can release funds from non-canonical fork states, exposing critical security vulnerabilities in cross-chain protocols.
Blockchain-Based Secure E-Voting System
January 1, 2024 – December 1, 2024
• Developed an Ethereum-based decentralized voting platform enabling tamper-proof vote recording. • Implemented voter registration and vote tallying using Solidity smart contracts and Web3.js. • Simulated election workflows using Ganache, validating execution across 1000+ test votes. • Measured smart contract execution cost at 387,957 gas per vote. • Impact: Prevents vote tampering and centralized control in electronic voting systems through immutable blockchain records.
Blockchain-Based Framework for Secure and Transparent E-Voting
IEEE
June 1, 2026 – Present
Sanskrit Mispronunciation Detection Using Alignment-Free Models
IEEE
June 1, 2026 – Present
Secure Network Framework Using Machine Learning for Intrusion Prevention
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and publications demonstrate a strong interest in cutting-edge technologies like blockchain and AI, as well as a commitment to impactful work (e.g., SanskritAI, secure e-voting). This aligns well with a culture that values innovation and social responsibility. The experience as a Full Stack Developer and Blockchain Developer shows adaptability and a broad skill set, which is beneficial for dynamic team environments. The academic focus, however, suggests a potential need for more exposure to commercial best practices and large-scale enterprise development workflows.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting strong problem-solving skills. The academic projects, particularly the cross-chain bridge attack simulation, demonstrate a proactive approach to identifying and addressing security vulnerabilities. The SanskritAI project shows initiative in applying technical skills to preserve cultural heritage, indicating a potential for impactful contributions. However, without direct assessment data on collaboration or communication in a team setting, it's difficult to fully assess operational fit beyond technical contributions.