Saksham Sarkar

Architected and optimized HealthRules Payor backend to maintain 99.98% uptime and meet SLA targets for healthcare claim processing. Migrated monolithic workloads from Azure VMs to Docker containers, reducing infrastructure costs by 60%. Designed Kafka-based workflows for inter-plan claim routing between BCBS Host and Home Plans, improving data exchange reliability. Implemented centralized observability via CloudWatch, Splunk, and New Relic, cutting mean-time-to-resolution by 40%. Enhanced CI/CD pipelines (Jenkins + Git) enabling blue-green deployments and faster release cycles.

Created a Kafka- and AWS Lambda-based QA Automation Platform with producer-consumer services, automating dealer website scraping through adaptive strategies; reduced manual QA effort by 60% and improved execution time by 40%. Developed a Model Orchestrator System using AWS SQS, S3, implementing event-driven workflows for vehicle image angle detection and background removal, improving image-processing efficiency by 35%. Designed asynchronous orchestration using Kafka, SQS, and SNS to achieve fault-tolerant, idempotent distributed workflows. Optimized a hybrid data layer using Redis caching and multi-database strategy (PostgreSQL, DynamoDB, MongoDB), enhancing system throughput. Deployed services via Docker and Kubernetes, integrating CloudWatch dashboards for 99.9% uptime and proactive alerting.

Led backend development for SAP SuccessFactors RCM, delivering scalable Job Requisition and Workflow Automation modules for enterprise clients. Architected Java-based Orchestrator Services using Chain-of-Responsibility, improving workflow modularity and reducing process latency. Delivered RESTful APIs, enabling automated deployments and real-time monitoring via Cloudwatch, Splunk, and New Relic. Built custom workflow templates and approval chains using configurable logic, streamlining HR operations like requisition, leave, and offer generation.