Revamped Causix microservice in Go to detect call types using AI inference, concurrently processing 10K+ calls per minute.
Orchestrated 11 microservices into a Compose stack, cutting onboarding time from 2 weeks to 1 day for QA and local setups.
Automated data recovery from PostgreSQL to ElasticSearch using goroutines, reducing effort from 5 days to 30 minutes.
Implemented IAM roles across 137 servers to replace AWS credentials after a security breach, enabling automatic key rotation.
Software Developer - Ministry of Electronics and Information Technology
Unique Identification Authority of India(UIDAI)
Bangalore
Jul 2023 — Sep 2024
Built and scaled a fraud detection microservice in Go, running AI inference to process 1,500+ biometric entries per minute and automate 85% of Aadhaar de-duplication via Kafka pipelines.
Optimized system performance using MySQL composite indexing and Redis-backed pipelines, achieving sub-50ms cache-miss latency and 30% higher throughput under stress.
Architected a secure HSM-encrypted biometric data pipeline (S3/Redis) with 80% test coverage, ensuring reliable and low-latency access across services.
Developed and deployed an operations portal from scratch, reducing manual workload by 75%, cutting DLQ processing time from 30 to 5 days, and improving efficiency by 40% with tracking and prioritization features.
Designed and deployed an Apache APISIX API Gateway on Kubernetes, managing 9,000+ daily requests, implementing routing, and enabling secure Keycloak-based token authentication in a three-legged auth flow.
Education
Indian Institute of Technology(IIT) Kanpur
Bachelor of Technology
Jul 2018 — May 2023
Skills
GoJavaJavaScriptHTML/CSSSQLGinGORMgRPCnet/httpReactNext.jsMySQLRedisKafkaElasticSearchDockerKubernetesJenkinsAWSPostgreSQLSIP TrunkingReactJSMUITailwindCSSKeycloakMiddlewareDevOpsApache APISIXMinIOCaddyAWS EC2AWS PollyAWS ASGGroq AI
Projects
Shorten
Developed a tool using Go and Next.js and GroqAI, to crawl webpages and generate structured markdown summaries.
Integrated AWS Polly via WebSocket to deliver Text-to-Speech and speech marks with word-level audio-visual highlighting.
Orchestrated infra with AWS ASG, Caddy, and Docker; used PostgreSQL and Google Analytics for latency and traffic analysis.
Achievements
Integrated Claude, Cursor, and Google Cloud into SuperPlane