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4+ years shipping ย ยทย  11 production systems ย ยทย  2 companies started ย ยทย  0 problems sent back unsolved


The Short Version

I'm not a task-taker. Give me a problem โ€” I'll come back with a shipped solution.

At Levo.ai I joined as a founding engineer before the product was defined. I talked to enterprise customers, found the gaps, and built the infrastructure they now depend on daily: kernel-level traffic sensors, API security engines, agentless discovery tooling, and a CLI built from zero. At IndiaMART, I ran ML search infrastructure at millions-of-queries-per-day scale.

I've also tried to build 2 companies. Both failed. Both taught me more than any job ever has.

Here's what 4+ years of owning problems end-to-end looks like:


Shipped โ€” Numbers Don't Lie

What Outcome
๐Ÿ”ฌ eBPF sensor with OpenSSL + BoringSSL TLS inspection (Levo.ai) TLS visibility across 60% of customer environments
๐ŸชŸ Windows PCAP sensor as a persistent Windows service (Levo.ai) +30% threat detection coverage across enterprise clients
๐Ÿ”Œ Native IIS HTTP/HTTPS kernel filter for enterprise IIS (Levo.ai) +40% observability โ€” wire-level traffic without touching app code
๐Ÿ›ก๏ธ GraphQL security engine โ€” auth, batching, introspection, injection (Levo.ai) REST + GraphQL + SOAP under one security engine
๐Ÿ› ๏ธ API security CLI, built 0โ†’1 (Levo.ai) Terminal-first: auth flows, traffic uploads, scan triggers
๐Ÿ“„ Agentless HAR-based API discovery (Levo.ai) +20% customer adoption by removing the agent install requirement
โšก Flask โ†’ FastAPI migration across services (Levo.ai) 45% latency drop, 2ร— request throughput
๐Ÿ“ก Signoz observability rollout across all applications (Levo.ai) 30% faster incident resolution across the team
๐Ÿ—„๏ธ Redis cache layer for ML search (IndiaMART) 40ms โ†’ 15ms โ€” 62.5% improvement at millions-of-queries scale
๐Ÿค– ML model + search API infra (IndiaMART) 98.9% uptime, +20% search accuracy, queries 30% faster
๐Ÿ“ฆ SQL data pipeline automation (IndiaMART) 90% of extraction automated, 60% manual effort eliminated

I've Also Tried to Build Companies

Most engineers write code. Fewer try to build products. I've done both โ€” and failed โ€” which is worth more than you'd think.

Build Verge Inc โ€” AI-Powered AEC Platform (with Stanford engineers)

Built an NLP + BIM platform to automate construction workflows using LLMs โ€” generating rooms, walls, doors, voids programmatically from language prompts. Ran into product-market fit and funding walls. The research lives on.

Washbe โ€” On-Demand Campus Laundry

Launched a React Native-based laundry platform with real-time scheduling. COVID hit. The market changed faster than we could pivot.

Both failed. I learned what you can't learn from any job: how to define a problem without a PM, talk to customers without a script, make architectural bets with no safety net, and keep shipping even when it's not working.

That's the founder mindset. That's what I bring to an engineering team.


Stack

Languages

Python Go TypeScript C/C++ Java

APIs & Backend

FastAPI Flask GraphQL gRPC Kafka RabbitMQ

Infrastructure & Cloud

Docker Kubernetes Helm AWS GCP Linux

Data & Storage

PostgreSQL MongoDB Redis

Observability

Prometheus Signoz Temporal

Low-Level & Specialty

eBPF PCAP TLS


GitHub Stats

Most production work lives in private Levo.ai repos. Public activity is open tooling, side projects, and experiments.

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Contribution Snake

GitHub contribution snake

Currently Exploring

type Focus struct {
    Topic string
    Why   string
}

currentWork := []Focus{
    {"eBPF + XDP",              "Wire-level packet processing โ€” no kernel modules, no overhead assumptions"},
    {"Agentic Debug Tooling",   "AI-assisted root cause analysis for live production incidents"},
    {"API Behavioral Drift",    "Detecting when APIs deviate from their established production baseline"},
    {"OpenTelemetry Internals", "What tracing frameworks actually do โ€” and what they still miss"},
}

Let's Talk

I'm looking for a team that's building something hard โ€” where the problems aren't solved yet, the architecture isn't locked in, and engineers are expected to think, not just execute.

If that's you, let's talk.

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