Leo Agentic Runtime
Built the real-time and durable execution layer behind the Leo Agentic Runtime: streaming, pooled tool connectivity, and restart-safe human review.
I build cool things on the internet - backends, side projects, and the occasional experiment that ends in WOW!. I’m stack-agnostic: Go one week, Python the next, something new after that. The hard part is figuring out what to build; the rest is just prompting.Currently a Senior Software Engineer at GEP Worldwide, shipping the kind of stuff I’d nerd out about on a weekend anyway.Outside work, I’m usually travelling, reading non-fiction, swimming, or trying to keep a gym routine alive.
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Senior Software Engineer at GEP Worldwide, based in India. I work on an AI agent orchestration builder platform, mostly around agent workflows, streaming experiences, tool integrations, and making complex systems feel easier to use.
Outside work, I’m usually travelling, reading non-fiction suspiciously slowly, or trying to balance gym, swimming, and pretending I have a routine.
I’m pretty sure AGI shows up eventually, so I’m trying my very best to understand where things are headed.
Senior Software Engineer · Go / C# / .NET / TypeScript / Elasticsearch
Built the real-time and durable execution layer behind the Leo Agentic Runtime: streaming, pooled tool connectivity, and restart-safe human review.
Designed the Elasticsearch layer spanning query orchestration, semantic search, and operational control for managed indices.
Built and operated a Logstash fabric consuming secured Kafka CDC topics (SCRAM-SHA-512) across 171 pipelines spanning 28 business domains - per-domain filter chains with 3-retry / 50s-timeout HTTP transforms feed a sync-strategy apply layer translating each change event into the correct Elasticsearch mutation.
A Go/Postgres durable execution engine purpose-built for AI agents - event-sourced replay, byte-exact divergence detection, and lease-based crash recovery with p99 < 50 ms RTT.
Earthquake precursor research from ionospheric signals using LSTM forecasting, anomaly detection, and SOM-based zone prediction.
A CNN-LSTM system combining finance-domain tweet sentiment with FOREX time-series signals to surface trading recommendations.