Cloud & Platform Infrastructure — AWS · Azure · GCP
I design cloud-native platforms and reliability engineering practices that ship faster, cost less, and stay up.
I engineer reliable, self-healing cloud infrastructure — designing platforms that scale gracefully, deploy fearlessly, and stay up when it matters most.
Building reliable platforms at scale.
Five years operating cloud infrastructure across fintech, healthcare, and enterprise workloads — from Kubernetes and IaC to SRE, observability, and cost optimization.
Koch Industries
DevOps Engineer / Site Reliability EngineerMar 2026 – PresentNew York99.9% uptime2× deploy freq-40% MTTR- Designing AWS and GCP cloud-native infrastructure, including virtual networks and Kubernetes-based container orchestration for analytics platforms supporting 10+ microservices across 3 environments.
- Implementing zero-downtime deployment strategies for containerized microservices using Kubernetes and automated CI/CD pipelines, increasing deployment frequency ~2× while maintaining 99.9% uptime.
- Building predictive monitoring and alerting using Prometheus, Grafana, and CloudWatch, improving anomaly detection and cutting incident response time by 40%.
- Managing Kubernetes clusters, container registries, and Docker/EKS/ECS ecosystems across 5+ clusters.
- Administering secrets management and access controls through cloud key vault services, cutting unauthorized configuration exposure incidents by ~20%.
- Collaborating with engineering and data teams on AI/analytics workflows, building model-serving infrastructure on AWS Fargate and Amazon SageMaker for three ML pipelines powering internal reporting tools.
Cerner Corporation
Cloud Platform EngineerMar 2025 – Feb 2026North Kansas City, MO+20% release velocity-25% MTTD-30% vulns- Built containerized infrastructure with Docker and Kubernetes (GKE) for distributed healthcare data-processing services across four production environments.
- Implemented CI/CD pipelines using Jenkins and Gradle, improving release velocity by ~20%.
- Designed observability dashboards using Prometheus, Grafana, and Splunk, cutting mean detection time by ~25%.
- Resolved distributed system issues across microservices, JVM services, and NoSQL databases, helping maintain 99.9% platform uptime.
- Partnered with security teams to harden infrastructure and container registry controls, reducing vulnerability findings by ~30%.
Citibank
Associate DevOps EngineerJun 2021 – Jul 2024Bangalore250K+ tx/day99.8% availability15h/wk saved- Supported AWS cloud infrastructure (ECS, OpenShift) hosting distributed banking analytics services processing 250,000+ daily transactions.
- Deployed containerized workloads using Docker and configured CI/CD pipelines, reducing manual deployment steps by ~30%.
- Automated infrastructure management tasks using Python, saving 15+ hours of manual effort per week.
- Monitored production systems using CloudWatch, maintaining 99.8% availability across financial transaction infrastructure.
- Maintained operational documentation and runbooks supporting incident response and audit readiness across 5+ compliance reviews.
The toolkit.
Hands-on across the full platform lifecycle — from cloud and containers to CI/CD, observability, and secure infrastructure at scale.
Cloud Platforms
Containers & Orchestration
Infrastructure as Code
CI/CD & Release Automation
Monitoring & Observability
Secrets & Security
AI/ML & MLOps Infrastructure
Scripting & Automation
Distributed Systems
// live-ish shell — for the ambience.
Things I've built.
Platform, reliability, and MLOps work — each project shipped with measurable impact.
Self-Service Internal Developer Platform
Backstage-based service catalog with scaffolding templates for 3 sample microservices and golden-path CI/CD templates (GitHub Actions + Terraform).
SRE with SLOs & Chaos Testing
Defined SLOs/SLIs, built an error-budget Grafana dashboard, and ran 10+ Chaos Mesh fault-injection experiments validating sub-30s recovery.
Multi-Cloud IaC & Cost Optimization
Reusable Terraform modules provisioning equivalent AWS/Azure stacks in under 15 minutes with automated right-sizing and cross-region failover.
MLOps + RAG Retrieval Pipeline
CI/CD pipeline integrating MLflow registry with Kubernetes model-serving, plus a FAISS-based RAG retrieval layer for low-latency semantic queries.
Academic background.
M.S. Computer and Information Science
Verified across AI, cloud & data.
Continuously credentialing on cloud platforms, AI/ML systems, and modern data engineering.
Let's build reliable systems together.
Open to DevOps, SRE, and Platform Engineering opportunities. Reach out about cloud infrastructure, Kubernetes, or MLOps roles.
saichandumachavarapu7@gmail.com