Alok Ranjan

I am a Senior Software Engineer with 7+ years of experience in backend engineering, large-scale distributed systems, data infrastructure, and ML pipelines. I specialize in building cloud-native platforms that are cost-efficient, reliable, and highly scalable—demonstrated by reducing compute costs by 37%, cutting ETL runtimes by 30%, and scaling concurrency 2× in production systems. Currently at Inspectorio, I design and implement event-driven architectures for supply-chain management platforms, improving scalability and responsiveness. At Thrasio, I re-architected a high-volume data lake ingesting 2+ TB monthly, eliminating redundant ETL stages and migrating workflows to Airflow on Kubernetes eventuality leading up to a cost savings of 500k$ anually. I also optimized Django microservices for Amazon Seller & Ads APIs, doubling throughput with gevent-based Celery workers and reducing pipeline runtimes via asyncio-based optimizations. At Level AI, I engineered a real-time ingestion pipeline processing over 100K+ Slack events per day, built a distributed secret store using HashiCorp Vault, and delivered compliance-ready retention systems. At Bright Money, I combined ML and systems engineering to design Spark- and Airflow-based pipelines for fund movement optimization and deploy quantile regression models for financial predictions. At Agility, I deployed NLP and computer vision solutions, including dual-attention transformer models for customs risk detection and multilingual text recognition using BERT variants. My core expertise includes Python, Go, SQL, Spark, Snowflake, Airflow, Kubernetes, Docker, Terraform, AWS, GCP, Kafka, RabbitMQ, and PyTorch. I thrive at the intersection of distributed systems, cloud infrastructure, and applied ML, consistently delivering systems that are production-grade, cost-optimized, and designed to scale.