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• Built an end-to-end automated outbound calling platform targeting churned merchants; integrated telecom APIs with an AI voice bot at 300 calls/min, with transcription and summarization into actionable buckets — driving 60% higher merchant engagement.
• Built a scalable vendor invoice ingestion and approval system using in-house LLM services; validated extracted data against POs with rule-based checks, routed conflicts for human approval, and auto-posted approved invoices — reducing processing costs 10x and turnaround time by 50%.
• Built a ledger accrual and vendor payout system with SFTP based Bank integrations (using Go, Kafka, DynamoDB, Redis) to automate disbursements for 10K+ vendors daily, eliminating 20 hours/week of manual reconciliation and reducing payout errors.
• Increased completion of critical SalesOps tasks by 35% by shipping a real-time push notification platform (Go + Kafka); designed idempotent consumers, retry/backoff, and rules-based routing so the right teams acted on the right events fast.
• Built a computer vision pipeline ingesting live CCTV streams to detect SOP breaches and trigger real-time alerts under 300ms latency, reducing warehouse pilferage costs by 30% within the first week.
• Improved reliability across a microservices stack by optimizing high-latency APIs (profiling + otel metrics) and remediating critical vulnerabilities in older systems.

• Successfully led a 20% increase in user subscriptions by developing a high-performance news streaming platform, ensuring real-time updates with less than 300ms latency through the utilization of Websocket as a Service and Pub/Sub architecture.
• Enhanced Postgres database operations to achieve a remarkable 3ms latency for reads/writes through indexing and partitioning techniques, optimizing overall system responsiveness.
• Created robust user session management using Redis, enabling seamless authentication and authorization processes while managing over 3,000 daily write operations and 15,000 daily read operations on the database.

• Achieved a 70% reduction in time-to-recovery from failed Risk and PnL jobs by developing a Flask-based API utility with thread pooling, local caching, and RQL for JP Morgan’s in-house trading platform.
• Improved system performance and data retrieval by utilizing an in-house distributed object store with indexing, resulting in a 100% increase in meeting End-of-Day SLAs.
• Enhanced overall system efficiency and reliability by implementing load balancing and optimized data processing frameworks to deliver high-impact business solutions.

• Built a GPT-3.5 powered e-commerce platform for an American fitness brand with 10+ virtual characters live on the platform.
• Built a custom branded ChatGPT app for a Brazilian EdTech company to integrate into their existing system.

• Write, develop, evaluate and document new and modified software programs running on the Openfabric Testnet chain.
• Developing a 3D Human Rotation AI App using HumanNeRF based architecture.
• Research, design and implement algorithms in deep learning for computer vision ang cutting-edge research.

MBON - Marine Biodiversity and Observation Network

• Building and maintaining Darwin Core Visualization python package - PyDwcViz, an open-source python package from scratch, adding 4 modules and 10 functions for providing easy one line analysis functions.
• Brought more than 7 features with a focus on OOP approach, creating 11+ Pull Requests and resolved 3 issues.
• Made it super easy for marine researchers to create diversity indices like Shannon's Index, ES50 (hulbert's index) with one-line functions.
• Plot DwC (Darwin Core) Data on a world map with built-in function, saving time and effort for researcher to focus only on the research and not struggling with writing the code for it.

• Rebuilt the complete pyobis python package - python client to OBIS API, with 100% endpoint coverage, ensuring quality by increasing the unit test coverage to 100% for all modules. github.com/iobis/pyobis
• Implemented 4 new features focusing on code quality, and successfully getting the release of a production package within a span of 12 weeks.
• Resolved more than 27 open issues, and successfully created 30 merged pull requests.
• Extrapolated data visualization tools to bring out research-grade analyses on migration patterns, time-series depth analysis, and species population among others from data captured through all 7 OBIS nodes globally