Geetansh Agrawal

• Spearheaded platform scalability to reliably support 1M+ daily assessment transactions by decomposing the monolithic evaluation engine into domain‑driven microservices, establishing clear service boundaries and enforcing idempotent REST interfaces for predictable request handling.

• Accelerated system throughput by 35% and eliminated workflow bottlenecks by orchestrating the transition of core evaluation flows to a distributed event‑driven architecture, leveraging Kafka/RabbitMQ with asynchronous message queues, consumer groups, and resilient dead‑letter mechanisms.

• Reduced database query latency by 40% and improved data throughput for 1M+ candidate records by restructuring workloads across MySQL (transactional) and MongoDB (document storage), optimizing indexes, implementing read/write separation, and integrating Redis‑ based hot‑cache layers for high‑frequency operations.

• Increased deployment reliability and minimized environment drift by adopting immutable Docker image builds, standardizing environment parity, and enabling zero‑downtime rolling deployments on AWS EC2 through automated CI/CD pipelines.

• Reduced response time by 25% and strengthened operational security by refactoring core modules using scalable design patterns and implementing RSA/AES encrypted logging with automated key rotation.

    CGPA: 8.23