Senior Software Engineer
Brief description of role and key responsibilities. Replace with your CV entries.
With two decades of experience in software engineering, I've dedicated my career to building reliable, scalable backend systems that power critical services in the financial and public sectors. My focus lies in modernizing legacy architectures—transforming monolithic constraints into event-driven, microservices-based solutions using Java, Spring Boot, Apache Kafka, and Apache Camel.
I believe that well-architected systems have the power to enhance global banking services, improving efficiency and reliability for millions. Whether it's adopting functional programming paradigms or designing resilient event streams, I approach every project with a commitment to technical excellence and long-term maintainability.
Brief description of role and key responsibilities. Replace with your CV entries.
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Summary of what you did and achieved. Add more items by copying this block.
Summary of what you did and achieved. Add more items by copying this block.
Summary of what you did and achieved. Add more items by copying this block.
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At Riskcare Ltd, I am leading the backend modernization of an FX trading platform, enhancing performance, scalability, and resilience through Java, Spring Boot, Kafka, and microservices.
At Capgemini, I played a key role in the microservices transformation of a MTD (Making Tax Digital) platform, converting a monolithic application into a scalable, event-driven system. I implemented REST APIs with Spring Boot and Apache Kafka, ensuring efficient service communication. My work included API development and management via Kong Gateway, implementing method-level metrics with Spring AOP to enhance monitoring and observability. I collaborated across teams to optimize microservices architecture, ensuring seamless integration and performance improvements. Additionally, I facilitated guilds and problem-solving sessions, promoting knowledge-sharing and best practices within the development teams. My contributions significantly enhanced system modularity, deployment efficiency, and API governance.
At RCDTS, I was responsible for managing hundreds of RESTful APIs using Apache Camel and Kong Gateway, significantly improving system integration and performance. I designed and implemented distributed system architectures using Spring Boot and microservices, modernizing legacy systems into scalable, maintainable services. I led API governance efforts, introducing modular design patterns and best practices to reduce system complexityand enhance maintainability. Additionally, I facilitated technical guilds and mentoring sessions, fostering collaborative learning and driving the adoption of modern development methodologies. My work in distributed data processing workflows ensured improved system reliability and scalability, strengthening the organization’s ability to process large volumes of transactions efficiently.
As an AVP at JP Morgan Chase, I played a crucial role in core banking software deployment and enhancements, focusing on middleware automation, developing integrations scripts in Java system security, and disaster recovery strategies. I spearheaded automation initiatives for release management, significantly reducing deployment time and minimizing manual intervention. I implemented SSL certificate management across critical banking platforms, ensuring secure communication between integration servers. I collaborated with global SA/DBA teams to deliver integrated solutions for payment gateways and SWIFT systems, enhancing operational resilience. Additionally, I orchestrated disaster recovery protocols, conducted resilience testing, and modernised deployment infrastructure, leading to a substantial reduction in system downtime and error rates.
At Cognizant Technology Solutions, I played a pivotal role in streamlining card issuance processes, ensuring secure data transfer to vendors and optimizing card personalization. I collaborated on data uploads, improving system accuracy and reliability, and facilitated seamless data flow, contributing to efficient card production. I managed data enrichment processes between AR systems, implementing FFN integration for Delta products and coordinating with multiple vendors for card embossing operations. I streamlined card processing operations by coordinating with multiple systems including Triumph, Optima, and CPP, enhancing data accuracy and delivery efficiency.
A quick snapshot of my current strengths, what I’m actively building with, and what I’m learning next.
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Developed an autonomous workflow orchestration system using LangGraph to eliminate repetitive manual processes. By creating graph-based agents that interface with JIRA, GitHub, and MongoDB, I reduced operational overhead on recurring tasks. This framework not only saved the company significant engineering hours but also established a scalable pattern for solving similar cross-platform automation challenges.
Implemented comprehensive tracing and monitoring to provide deep system visibility. By integrating Grafana, I established real-time performance dashboards and alerting, significantly reducing mean time to resolution (MTTR) for production issues and improving overall system reliability.
Actively using for 2+ years across automation and AI projects. Proficient in writing scripts, building LangGraph workflows, and integrating with APIs (JIRA, GitHub, MongoDB). Continuously deepening expertise to support agentic AI development.
Actively leverage GitHub Copilot to accelerate development workflows, from boilerplate generation to complex algorithm implementation. Proficient in prompt crafting, context management, and leveraging Copilot's inline chat, slash commands, and workspace features to write cleaner, more efficient code across Java, Python, and backend frameworks.
Focussing on learning/understanding the Gradient Descent, Polynomial Regression Algorithms.
My objective is to design and deploy custom MCP servers to create a bidirectional data plane between AI agents and internal/external tools.
Currently planning to build proficiency in PyTorch and TensorFlow/Keras to extend my automation and agentic AI work into the deep learning domain. starting to understand neural network architectures, model training, and integration with existing LLM workflows.
Drop me a line — I’d love to hear from you.