* High-Scale Systems: Own reliability, efficiency, and AI-driven automation for distributed ingestion services processing 10-20 TB/s scale data across 10+ global regions.

* Efficiency & Sustainability: Engineered throughput-based autoscaling algorithms for 100k+ servers, increasing CPU utilization from 15% to 40% and delivering >4 MW in peak-hour power savings.

* Agentic AI Integration: Designed and productionized Agentic AI systems (Claude Opus-based) to automate on-call triage and support, reducing critical alert interventions by over 50%.

* Disaster Recovery: Led a team of 5 to build autonomous failover workflows, achieving 99.99% DR readiness (10x improvement over 2 years) for large-scale ingestion services.

* Leadership & Mentorship: Mentored 50+ graduates via the MLH Fellowship (50% full-time conversion) and partnered with leadership to double the size of the ingestion team.

* Developed real-time tracing for ~5TB/s ingestion pipelines, reducing issue diagnosis time from hours to minutes.

* Designed unified distributed traces across data‑generation pipelines, improving reliability and efficiency

• Developed Operator Verification Library from the ground up written in Golang to provide static off-cluster verification of the operator manifest

• Improved operator developer experience by providing a quick feedback loop on manifest errors and a single definition of a valid operator manageable by the Operator Lifecycle Manager (OLM)

• Developed a command-line tool as one of the ways of interacting with the library

Application Development for Information Security Management using C# and .NET Core.

I developed lab exercises pertaining to microservices and their deployment using various cloud technologies.