Building production-grade AI systems, automating infrastructure, and designing scalable distributed applications
I'm a Staff-level engineer focused on AI infrastructure, DevOps automation, and scalable system design. I design and deploy end-to-end solutions—from AI-powered applications to automated deployment pipelines—with a focus on reliability, performance, and operational excellence.
My expertise spans AI/ML engineering, cloud infrastructure automation, and system design for high-availability environments. I architect systems that are technically sound, cost-efficient, and built to scale.
A complete Notion system for developers, students and job seekers.
✅ Habit Tracker
✅ Job Tracker
✅ Project Planner
✅ Learning Roadmap
👉 Get it here:https://ronniesingh4.gumroad.com/l/ibffk
learning:
- Applied ML with production datasets (feature engineering, model monitoring)
- AWS serverless architecture (Lambda, API Gateway, DynamoDB)
- Cost optimization strategies for cloud workloads
- System design patterns for high-scale distributed systemsbuilding:
- AI voice agents with streaming inference
- IaC pipelines with Terraform modules
- CI/CD workflows for ML model deployment
- Observability stacks (Prometheus + Grafana)"Optimize for correctness, clarity, and maintainability. Scale comes from architecture, not shortcuts."
I believe in writing production-ready code from day one—systems that are resume-worthy, interview-ready, and actually deployable. No toy examples, no MVP thinking. Just solid engineering.
Open to discussing:
- AI/ML infrastructure and MLOps best practices
- Cloud architecture reviews and cost optimization
- DevOps automation and CI/CD pipeline design
- System design for high-traffic applications
Reach out:msrawat.devops@gmail.com
