• Designing and developing high-scale distributed middleware systems using Python, Go and C++, serving as the integration layer between consumer product platforms and ML inference infrastructure, processing billions of daily requests with sub- 100ms p99 latency across Kubernetes clusters on GCP.

• Implementing a GraphQL API Gateway in Go, orchestrating data flow across 10+ upstream machine learning model serving systems and cross-functional product teams (Feed, Reels, Ads), improving service decoupling, API standardization and schema governance.

• Built and optimizing real-time ML feature serving pipelines in Python backed by NoSQL databases, reducing feature retrieval latency by 35% and eliminating training-serving skew in large-scale ranking and recommendation systems.

• Developing performance-critical middleware components in C++, enhancing data serialization, memory optimization, inter- process communication (IPC) and internal RPC frameworks, increasing throughput and efficiency at billion-request scale.

• Designeding and implementing Service Level Objectives (SLOs), observability, and resilience engineering patterns using Prometheus, Grafana, Docker and Kubernetes, incorporating circuit breakers and fallback mechanisms to reduce cascading failure impact by 45%.

• Strengthening platform security and API governance by implementing mTLS, token validation, adaptive rate limiting and

data protection controls, ensuring compliance with enterprise security standards.

• Collaborating within an Agile/Scrum engineering team, conducting system design discussions, UML modeling, GitHub pull requests and SonarQube code quality reviews, reducing review cycle time by 30% and improving development velocity.

• Designed and developed high-availability, high-throughput payment processing microservices using Java, Spring Boot, Kubernetes and AWS, supporting millions of daily POS transactions with 99.9% SLA uptime compliance.

• Architected and maintained RESTful APIs and GraphQL services to enable EMI, Buy Now Pay Later (BNPL) and multi-issuer payment integrations, reducing transaction failure rates by 25% and improving payment reliability.

• Developed real-time merchant analytics dashboards using React.js, TypeScript and Tailwind CSS, backed by PostgreSQL and

Amazon RDS, optimizing SQL queries to support transaction reporting for 10,000+ merchants.

• Implemented secure API authentication and authorization using Spring Security and OAuth 2.0, ensuring PCI-DSS compliance, data encryption, and secure handling of cardholder data across distributed systems.

• Established observability and monitoring frameworks using Prometheus, Grafana, Docker, Kubernetes and Rancher, reducing Mean Time to Detection (MTTD) of production incidents by 35% and improving system reliability.

• Strengthened CI/CD pipelines using GitLab, SonarQube, automated testing and code reviews, contributed to data modeling and UML design, and reduced technical debt across 3 Agile/Scrum cross-functional engineering teams.

• Developed and maintained scalable backend microservices using Java, Spring Boot, Spring MVC and RESTful APIs, supporting high-traffic e-learning applications with thousands of concurrent users.

• Built dynamic and responsive front-end applications using Angular, JavaScript (ES6+), HTML5, CSS3, Bootstrap and AJAX, improving user experience and reducing page load time by 30%.

• Implemented secure authentication and authorization using Spring Security, Role-Based Access Control (RBAC), and JWT, enhancing application security and reducing unauthorized access.

• Containerized applications using Docker and deployed to AWS (EC2, S3, IAM), improving CI/CD workflows and reducing environment setup time by 40%.

• Designed and optimized relational databases (MySQL, PostgreSQL), wrote complex SQL queries and stored procedures, and performed performance tuning to support analytics and reporting systems.

• Participated in the full Software Development Life Cycle (SDLC) within an Agile/Scrum environment, leveraging Git, GitHub, code reviews, and Postman to ensure code quality and reduce post-release defects by 20%.