Building scalable cloud infrastructure and data-heavy platforms for FinOps and SaaS
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I'm an Infrastructure Lead at FinOpsly AI, building and scaling cloud infrastructure for a FinOps SaaS platform. My expertise spans AWS (EKS, VPC, RDS, CloudFront, WAF), Snowflake, Kubernetes, Terraform, and CI/CD—with a focus on cost optimization, data-heavy architectures, and zero-downtime deployments.
With a B.Tech in Computer Science and hands-on experience across DevOps, ML pipelines, and analytics, I specialize in designing scalable infrastructure, real-time data pipelines, and observability stacks that keep production reliable and secure.
Fantasy gaming platform for 20M+ users. I built AWS EKS infrastructure with Istio, Kafka/NATS, Aurora PostgreSQL, Redis, and full observability.
Smart home IoT platform for lights, climate, and security. I designed DevOps architecture with MQTT, device gateways, and event processing.
Tool to protect sensitive data from unauthorized access. I owned DevOps for all tiers and set up VMUA.
Timecard and fleet solution for truck hours, loads, and cost vs budget. I managed DevOps infrastructure and microservices.
Restaurant tool for invoices, product discovery, and price comparison. I managed AWS with Terraform and CI/CD (GitHub Actions).
E-signing and notarization SaaS for legal, fintech, and healthcare. I built and scaled Kubernetes microservices.
CV parsing and job-description matching with ML. I architected the pipeline using Django and vector databases.
Moving and relocation company (residential, commercial, employee relocation). I automated deployments and CI/CD on Azure, migrated on-prem to cloud, and automated tasks with Shell scripting.
Fabric anomaly detection during manufacturing to reduce wastage. I managed the data pipeline (MQTT → InfluxDB) and real-time monitoring in Grafana.
CGPA: 8.5/10
CGPA: 8.5/10
There are only two hard things in Computer Science: cache invalidation and naming things.
Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it.