BENEATH THE INTERFACE
My foundation is systems engineering: memory layouts, protocol boundaries, timing, and failure modes. I bring that same rigor to product and applied AI work.
TATA CONSULTANCY SERVICES / NSE INDIA
July 2021 to August 2023. Systems Engineer embedded at the National Stock Exchange, working on its commodities and derivatives matching engine under a senior architect.
ENGINEERING PRINCIPLES / LEARNED IN PRACTICE
Changes to a shared-memory structure affect every process reading it. At NSE, my work included auditing message types and preserving structure compatibility across the engine’s layers.
C · shared memory · protocol evolutionRolling out AES-256-GCM required thinking beyond encryption correctness. I worked on latency equalization so encrypted and unencrypted channels did not gain different timing advantages.
AES-256-GCM · timing · systems integrationI built a C/C++ benchmarking injector to isolate layer behavior, then used the results to investigate system noise, CPU pinning, and IRQ balancing.
Benchmarking · clock_gettime · LinuxDisaster-recovery drills, configuration alignment, backups, and Jenkins pipelines made operational behavior part of the engineering work.
DR · release automation · repeatabilityCORRECTNESS UNDER CONSTRAINTS
I also worked on Market Price Protection, shared-memory debugging with GDB, peer review, and regression testing across engine layers. The constraint was not just to add behavior, but to preserve the surrounding system’s timing and data contracts.
This is the perspective I now bring to AI features: define the boundary, inspect the failure path, and verify the output before trusting it.
See that thinking in Tailorbird ↗This account is based on the supplied resumes. NSE was the client engagement through TCS, not my direct employer. System transaction volume describes the engine, not a personal throughput achievement. Proprietary source, topology, and operational details are not published.