Headline

Senior Software Engineer at American Express | Backend Systems | Microservices | Cloud (GCP, Kubernetes, Docker) | Building Reliable & Scalable Platforms

About

🚀 Software Engineer with 5+ years of experience building large-scale, high-performance backend systems and distributed platforms-specializing in fraud detection, credit risk, and low-latency transaction processing. I’ve architected systems processing 30M+ events/day on Google Cloud, driving measurable business outcomes through scalable, reliable software design. 📍 At American Express, I’ve: • Architected a real-time transaction processing platform on GCP (Pub/Sub, Dataflow, microservices), reducing response latency from 15s to under 5s • Built event-driven APIs and distributed pipelines with Spring Boot, FastAPI, and Kotlin, improving approval accuracy by 15% and cutting false positives by 17% • Established CI/CD pipelines and observability stacks (Cloud Build, GitHub Actions, Prometheus, Grafana, ELF Logging) to enable faster, safer deployments • Mentored engineers in system design, observability, and incident response, strengthening platform resilience and team efficiency 🛠️ Technical Expertise: Languages: Java, Kotlin, Python, SQL Frameworks: Spring Boot, FastAPI, Flask, gRPC Cloud & Infra: GCP (Pub/Sub, Dataflow, BigQuery), Kubernetes, Docker, Terraform Data & Streaming: Kafka, Spark, Airflow, Hive DevOps & Monitoring: GitHub Actions, CI/CD, Prometheus, Grafana, ELF Logging ⚙️ I’m passionate about backend craftsmanship, distributed systems, and scalable architecture—engineering reliable, low-latency services that deliver real business impact at scale. 🤝 Always keen to collaborate on systems that combine robust design, real-time data flow, and operational excellence.

Location

Gurugram

AI stack

antigravity

claude code

claude

codex

cursor

github copilot

Work experience

Senior Software Engineer at American Express, May 2023 - Present · 3 yrs 4 mos, India · Hybrid, - Architected and led the design of a real-time transaction processing platform on GCP (Pub/Sub, Dataflow, microservices), handling 30M+ events/day and reducing response latency from 15s to under 5s. - Spearheaded the development of an A/B infrastructure framework with telemetry, feature flags, and automated rollback for credit-risk APIs-boosting approval accuracy by 15% and cutting false positives by 17%. - Implemented and scaled CI/CD pipelines using Cloud Build and GitHub Actions, enabling a 3× increase in release velocity while maintaining 99.99% uptime and zero Sev-1 incidents. - Enhanced observability and reliability through ELF logging, Prometheus, and Grafana, improving incident detection and response times by 40%. - Mentored and guided a team of 4+ engineers on modular backend architecture, distributed tracing, and operational excellence, fostering a strong culture of system ownership and scalability.

Software Engineer at American Express, Aug 2021 - May 2023 · 1 yr 10 mos, India · Hybrid, - Engineered and optimized distributed data processing pipelines using Airflow and BigQuery, improving compute efficiency by 75% (6 hrs to 90 mins) and accelerating quarter-close by 2+ days. - Developed and maintained scalable backend services with Spring Boot, Kotlin, and Python, integrating credit-risk scoring APIs into underwriting workflows-reducing early delinquencies by 12% across key markets. - Designed and implemented real-time monitoring and alerting pipelines with SLA enforcement, retry logic, and failover recovery, achieving 99.9% uptime across finance and risk data systems. - Automated data aggregation microservices powering analytics dashboards through BigQuery BI Engine, cutting fraud investigation response times by 40% and improving decision-making speed. - Collaborated cross-functionally with data, risk, and product teams to align technical execution with business objectives, ensuring reliability, scalability, and compliance of critical backend platforms.

Software Engineer Intern at American Express, Jan 2021 - Jun 2021 · 6 mos, India, - Redesigned legacy reporting workflows by implementing a streaming-based architecture for real-time risk dashboards, improving data freshness and reducing report latency by 60%. - Developed and optimized data processing pipelines in Python and SQL, refactoring business logic and queries to reduce execution time by 50%. - Built automated data validation and profiling frameworks, improving pipeline reliability, data quality, and reducing manual QA overhead. - Collaborated with senior engineers to propose modernization strategies for risk analytics platforms-laying the foundation for scalable, event-driven reporting systems.

Education

Bachelor of Engineering, Computer Engineering, Thapar Institute of Engineering & Technology

High School, Non-medical (PCM), L.R.S. D.A.V. Sr. Sec. Model School