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• Revamped research agent architecture, reducing API calls by 67% (from 3 to 1 per query) and saving over ₹20,000 per month in inference costs, while cutting per-request cost by 90% and improving response latency by 75%.
• Built a high-scale async research engine using Python AsyncIO with 150 concurrent workers, SQS batch processing (100/msg), Redis distributed locks, exponential backoff retries, DAG-based orchestration, and multi-level caching; processing millions of datapoints weekly.
• Deployed three specialized research pipelines tailored to distinct query categories, increasing retrieval relevance by 22%, improving factual coverage, and boosting overall answer quality across production workloads.
• Engineered cross-service credit deduction pipeline across three microservices through checkpoint-based aggregation and idempotent upserts, eliminating duplicate charges while synchronizing balances within 60 seconds.
• Devised a comprehensive LLM evaluation framework featuring a two-stage "LLM-as-Judge" architecture with Perplexity Sonar Pro for web fact verification and GPT-5 for structured evaluation, enabling parallel A/B benchmarking across 8 model variants and cutting manual evaluation effort by 80%.
• Delivered 15+ production enhancements to React.js interfaces for job recommendations and worker dashboards, reducing First Contentful Paint from 1.4s to 0.9s and Time to Interactive from 2.4s to 1.6s, reaching a 92/100 Google Lighthouse score.
• Integrated REST APIs for job and worker matching, processing 15K+ requests/day with an average response latency of 120 ms.
• Spearheaded development of Siamese Neural Network in PyTorch for patient verification system, achieving accuracy rate of 98.6% through rigorous testing and validation of core ML components across 5,000+ patient records.
• Engineered backend services with Node.js and Express.js, designing hospital system integration architecture that enabled 400+ daily patient transactions while maintaining 99.5% system uptime.
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Event-driven microservices platform for banking exam preparation: an API gateway and five Fastify services over schema-per-service PostgreSQL, Kafka with a transactional outbox for exactly-once event delivery, Redis for rate limiting and leaderboards, and job-based question generation with Google Gemini.
Terminal-first and headless coding-agent CLI and persistent session harness. Features interactive TUI, 45+ slash commands, subagents in isolated git worktrees, streaming execution, and multi-model BYOK support.
Production-grade event photo-sharing platform for photographers and guests. Attendees scan a QR code and take a selfie; facial recognition (SCRFD + ArcFace 512-d embeddings, FAISS indexing) instantly surfaces only their photos. Built with Node.js/Express, Flask ML microservices, React, and MongoDB.
Browser-based arbitrary style transfer running entirely client-side in TensorFlow.js — no images ever leave the device. Four convertible models (56MB total) are exposed as a speed-versus-quality choice and loaded lazily, with two-style blending performed in style space rather than on pixels.
About
0 to 1 builder and software engineer with a passion for building scalable, high-performance systems. LeetCode Rating: 1760 and CodeChef 5-star (Rating: 2040). Specialized in optimizing backend architectures, database performance, and algorithmic efficiency. Expertise in C++, Node.js, FastAPI, and PostgreSQL optimization.
Skills
shivbera18's GitHub & LeetCode journey over the past year
Fetching your coding activity data
Solving algorithmic challenges and building efficient solutions
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A simple, practical look at how search engines work, why Instacart replaced Elasticsearch with Postgres, and how they actually made it 2x faster.
A practical framework for evaluating database paradigms, CAP/PACELC trade-offs, and real-world system architecture case studies.
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