SRE & Production Engineering
Incident response, on-call support, root-cause analysis, SLO/SLI design, runbooks, chaos and load testing, production support during market hours.
Systems / Production Engineer
Building reliable, real-time distributed systems for production environments.
I support high-performance platforms across Linux, Kubernetes, AWS, Kafka, and observability stacks. My work spans automation, incident response, production engineering, and performance tuning for data-intensive systems.
- 7+ years supporting production systems
- 99.99% uptime across Kubernetes and AWS workloads
- Strong in Python, Bash, Kafka, Prometheus, Grafana, and Linux
Core Focus
Site reliability, cloud operations, observability, and low-latency distributed systems.
45%
MTTR reduction through automation
60%
On-call paging reduction
1M+
Events/day in data pipelines
100K+
Users supported in production
About
Operationally calm, technically deep, and outcome focused.
I am a systems and production engineer with experience supporting high-performance, real-time distributed systems on Linux, Kubernetes, and AWS. I build operational tooling in Python and Bash, investigate complex incidents, and work closely with engineers, traders, and research teams to improve platform reliability, speed, and resilience.
My background combines software engineering, infrastructure, automation, observability, and production support. I enjoy turning noisy operational problems into repeatable systems, robust runbooks, and measurable reliability gains.
Skills
Technologies and production strengths
Scripting & Automation
Python, Bash, Go (familiar), Ruby, operational tooling, workflow automation, Ansible, Terraform, deployment and recovery scripting.
Linux & Kubernetes
Linux systems administration, Kubernetes debugging, Helm, operators, Docker, systemd, networking, DNS, firewalls, and performance tuning.
Observability & Messaging
Prometheus, Grafana, Splunk, OpenTelemetry, ELK, Apache Kafka, alerting, dashboards, and log aggregation.
Cloud & Data
AWS, Azure, GCP, PostgreSQL, Oracle, MySQL, MongoDB, Redis, CI/CD with Jenkins and GitHub Actions.
Trading Domain
Market data feed handlers, CME MDP 3.0, FIX protocol, tick and bar data, low-latency trading workflows, market microstructure.
Experience
Selected professional experience
Software Engineer · Sprouts AI
Chicago, IL
- Support 20+ production microservices on AWS EKS during live operating hours with 99.99% uptime.
- Built Python and Bash automation for deployments, log collection, and incident response, reducing MTTR by 45%.
- Resolved issues across Kafka pipelines and Kubernetes workloads, cutting recurring incidents by 40% through postmortems and platform hardening.
Software Engineer · Resilience Inc
Chicago, IL
- Operated a real-time market-data pipeline across Kafka, Kubernetes, and PostgreSQL, maintaining sub-second data freshness SLOs during market hours.
- Authored Python/Bash automation and Kubernetes operators for auto-remediation, reducing on-call paging by 60%.
- Partnered with traders, quants, and engineers to investigate latency spikes using Prometheus, Grafana, perf, strace, and tcpdump, improving tick-to-trade latency by 30%.
- Built self-service tooling for safe deployment and monitoring of strategy jobs, eliminating 10+ weekly tickets.
Software Engineer / IT Project Manager · Tata Steel
Remote
- Operated cloud-native Java microservices on Kubernetes with 99.99% uptime across 100K+ users.
- Built Kafka and PostgreSQL-backed data pipelines processing 1M+ events/day with Python/Bash runbooks and Ansible playbooks.
- Led Agile SDLC adoption using Git, Jenkins, JUnit, and Pytest, reducing release lead time by 60% and mentoring engineers on reliability practices.
Projects
Work that reflects my systems mindset
CME MDP 3.0 Multicast Market-Data Feed Handler
C++20 · Low latency · Trading infra
A low-latency feed handler that decodes live CME tick data using lock-free queues, per-instrument threading, and seqlock snapshots to support real-time trading-system workflows.
View on GitHubTradeSentinel
Observability · Kubernetes · Kafka · Python
An observability platform for trading systems showing order flow, latency distributions, pod health, Kafka lag, and Prometheus alerts, with auto-remediation utilities for common production failures.
View on GitHubPublication
Research contribution
Comparative Study of Movie Recommendation System Using Feature Engineering and Improved Error Function
IEEE INCOFT 2021 · DOI: 10.1109/INCOFT55651.2022.10094480
Education
Academic background
M.S. in Computer Science
Illinois Institute of Technology
B.Tech in Computer Science
National Institute of Technology, Calicut
Contact
Let’s connect.
I’m open to software engineering, systems, SRE, production engineering, and trading infrastructure opportunities.