Senior Software Engineer Wissen Technology — Client: JP Morgan (Mar 2025 – Present)
Domain: Asset & Wealth Management | Stack: Java (Moneta Boot), AWS, Redshift, GraphQL, Grafana, Splunk, Jules, Gaia, MCP, GenAI, Copilot
- Redesigned CI/CD deployment pipeline to enforce mandatory post-deployment test validation gates using the Karate framework, reducing integration failures reaching production by 45% and cutting release cycle time by 20%.
- Leveraged Generative AI tools (GitHub Copilot, MCP, DevGPT) across the backend team to accelerate feature delivery by 30%, improve code quality scores by 25%, and reduce PR review turnaround from 3 days to 1 day.
- Collaborated cross-functionally with QA, DevOps, and product teams at JP Morgan to define coding standards and release readiness criteria, improving deployment confidence across 4 squads.
- Actively led technical hiring — conducted 20+ engineering interviews, evaluated system design and coding competency, and collaborated with leadership on candidate calibration.
Domain: CDN & Load Balancer Infrastructure | Stack: Java (Spring Boot), Python, Terraform, Kiev, Grafana, Kibana
- Led a team of 6 engineers to architect and deliver an end-to-end automation tool for deploying a critical CDN component across 30+ OCI regions, achieving a 70% reduction in deployment time and eliminating 100% of manual deployment errors.
- Designed and managed a comprehensive observability stack (Grafana, Kibana, Splunk) to monitor CDN services handling 100K+ RPS, maintaining a 99.95% availability SLA and enabling real-time fault detection.
- Improved system reliability and on-call efficiency by authoring 15+ runbooks, enhancing alarm signal-to-noise ratio, and implementing 25 new alarm metrics — reducing MTTR by 40% and on-call incident volume by 30%.
- Analysed customer requirements and translated them into technical solutions and architectural strategies; presented roadmap proposals to senior stakeholders, influencing infrastructure investments across two quarters.
- Mentored and guided 4 junior engineers on distributed systems design, cloud best practices, and operational excellence — fostering a knowledge-sharing culture that improved team velocity by 25%.
Software Engineer-3 Walmart Labs (Dec 2019 – Feb 2022)
Domain: E-commerce Order Management | Stack: Java (Spring), Python, Terraform, Cassandra, Kafka, Redis, Splunk
- Architected migration of a legacy monolith to a Java 17 microservices platform for Canadian and Mexico markets, reducing system latency by 35%, supporting 5M+ daily transactions, and enabling independent deployment of 8 services.
- Designed and implemented a high-throughput Disaster Recovery system leveraging Kafka and Cassandra to replay 500K+ orders within a 15-minute RTO — ensuring 99.95% uptime and full business continuity during regional failover events.
- Secured REST/gRPC database APIs using audit logging, role-based access controls, and Istio service mesh enforcement, achieving zero unauthorized-access incidents over a 2-year period.
- Runner-up at Walmart Global Hackathon 2020 & 2021, competing against 2,000+ engineers globally.
Software Engineer-2 iQuanti (Feb 2019 – Dec 2019)
Domain: SEO Analytics | Stack: Python, Django, AWS, MongoDB, Airflow, Redis
- Developed, tested, and deployed 8+ backend components of the ALPS SEO platform using Python and Django, improving crawl analysis throughput by 25% and reducing page load evaluation time by 30%.
- Optimised the core SEO content simulation module using Redis caching, achieving a 40% reduction in score calculation time and significantly improving platform responsiveness at scale.
- Designed and delivered multiple RESTful APIs for the content simulation module, enabling seamless integration with downstream analytics tools and reducing inter-service latency.
- Coordinated cross-functional testing with QA and product teams, ensuring compliance with SEO industry standards and reducing post-release defect rates by 20%.
Domain: AI-Driven Scheduling & Data Enrichment | Stack: Java, Python, Pandas, ETL, MySQL
- Managed backend database and business logic for CinemaAI — an AI-powered movie scheduling platform — and developed schema transformation pipelines for 15+ payload types to support data enrichment workflows.
- Built a Python-based automated report generator that reduced manual reporting effort from 4 hours to under 15 minutes per week, saving 180+ engineering hours annually.
