Building operational systems
across data, infrastructure, and realtime platforms.
Focused on building reliable systems across realtime ingestion, analytics infrastructure, automation workflows, and production-scale data operations.
CTO @ Saras • Apple • IIT Bombay
About
I'm an engineer focused on building operational systems that remain reliable under real-world constraints.
After working across analytics and operational infrastructure at Apple, I moved into a leadership role as CTO and Co-Founder at Saras, where I helped build and scale the platform from scratch.
My work has primarily focused on realtime ingestion systems, execution infrastructure, analytics workflows, automation tooling, and production data pipelines.
I enjoy solving problems that sit at the intersection of scale, reliability, and operational complexity.
Timeline
Saras
Sept 2024 — PresentCTO, Co-Founder
Built a signal intelligence platform that captures, parses, and virtually executes trading recommendations across multiple sources. 150K+ downloads, 200K+ daily messages received, <500ms execution latency, 20K concurrent users, 600+ APIs, 98% uptime.
Apple
Jan 2022 — July 2024Consulting Data Engineer → Data Scientist
Sole data engineer for an AppleCare analytics org — ~20 production pipelines, ML-based KPI anomaly detection, and an NLP classification pipeline processing 400K+ items daily with a 68% runtime cut.
Testbook
Aug 2020 — Jan 2022Analyst
Owned event instrumentation for 6M+ monthly active users — Redash dashboards on MongoDB, and self-taught automation powering sales operations.
OYO
Jun 2019 — Jul 2019Summer Analyst
Scraped OTA listing data and ran ranking-analysis experiments — my first hands-on exposure to real-world data problems, and where I taught myself SQL.
EY
May 2018 — Jul 2018Summer Associate
Built my first working system without prior coding experience as part of a national-scale education platform initiative.
Systems & Operational Work
Realtime Recommendation Ingestion
Realtime ingestion and parsing infrastructure for transforming noisy multi-source recommendations into structured trading signals.
Virtual Trade Execution Engine
Execution infrastructure for managing concurrent trade lifecycle simulation, follow-ups, and realtime state transitions.
Multidimensional Analytics Infrastructure
Redis-powered multidimensional filtering and analytics infrastructure optimized for realtime operational querying.
KPI Anomaly Detection
ML-assisted anomaly detection workflows for operational KPI monitoring and automated stakeholder alerting.
Social Listening Classification
Operational ML pipelines for classifying product issues, feature-level signals, and social conversations at scale.
Product Instrumentation & Analytics
Event instrumentation, analytics workflows, experimentation tracking, and operational reporting systems.