Raj B.

~10,000 daily users. ~$430K in unauthorized transactions. Production restored in 1–1.5 days. That's one of the high-stakes AWS production environments I've helped secure. As a key technical responder during a critical AWS + Fireblocks security incident, I investigated suspicious cloud infrastructure using CloudTrail, secured privileged access, rotated compromised or high-risk credentials, hardened IAM permissions, and helped restore production operations. No further unauthorized transactions were observed after remediation. I'm an AWS Cloud & AI Engineer and Python Backend Developer with 25+ Upwork projects, specializing in building, deploying, securing, and scaling production-ready AI applications on AWS. A few projects I've successfully delivered: ✅ AWS Security Incident Response — ~10,000 Daily Users Helped contain and remediate a critical privileged-access incident involving approximately $430K in unauthorized transactions. Investigated ECS/RDS infrastructure, rotated credentials, strengthened AWS IAM and Fireblocks access controls, and helped restore production within approximately 1–1.5 days. ✅ AI Model Deployment — 3 Models, Up to 2 GB Each Designed an independently scalable model-serving architecture using Amazon ECS and SageMaker Serverless Inference. Separated Python backend workloads from AI inference to improve resource efficiency and avoid continuously running model servers. ✅ AI Photo Platform — 5 Lambda Processing Groups, 3 AI Models Architected an AWS serverless pipeline using S3, SNS, SQS, and Lambda for asynchronous AI image processing, vector embeddings, semantic search, and metadata generation. Designed 2 independent processing paths to avoid unnecessary AI compute and optimize infrastructure costs. ✅ Production DevOps & AWS Automation Implemented Git-based CI/CD pipelines, Docker deployments, Python 3.12 runtime standardization, workload-specific resource optimization, and least-privilege IAM security. My Core Expertise AWS AI/ML: SageMaker, AI model serving, inference pipelines, LLM deployments, and AI infrastructure Python Backend: FastAPI, Flask, REST APIs, asynchronous processing, and backend automation Generative AI: OpenAI APIs, LangGraph, RAG, AI agents, FAISS, and Pinecone AWS Infrastructure: Lambda, ECS, S3, SNS, SQS, RDS, IAM, and serverless architecture DevOps: Docker, Terraform, CI/CD, infrastructure automation, and monitoring AWS Security: CloudTrail, incident response, IAM hardening, credential rotation, and cloud security audits I don't just deploy applications to AWS. I build the backend systems, AI infrastructure, and cloud architecture required to run them securely and reliably in production. If you need to deploy AI models, develop a Python backend, architect an AWS platform, or improve your existing infrastructure, let's discuss your project.