I am a Cloud & DevOps Engineer with deep foundations in Automated CI/CD, Containerization, Kubernetes Orchestration, and Infrastructure as Code (IaC) — combined with hands-on expertise in Applied AI/ML and MLOps.
- ☁️ Cloud & Infrastructure (Primary): AWS cloud architecture (VPC, EC2, ECS, ECR, S3, ALB), Terraform modular IaC, Docker multi-stage builds, and Kubernetes orchestration with Helm charts.
- 🔄 Automation & CI/CD: Enterprise 7-stage Jenkins pipelines with Trivy security auditing, GitHub Actions workflows, and Linux bash automation.
- 📈 SRE & Observability: Real-time health monitoring, metric scraping, and dashboarding with Prometheus, Grafana, and AWS CloudWatch.
- 🤖 Applied AI & MLOps: Production-ready multi-agent architectures using LangGraph, FastAPI, Redis, ChromaDB, and MedGemma.
🎯 Open to: Full-Time Cloud & DevOps Engineer roles and Semester Internships (Immediate Joiner · Open to onsite & remote).
MAIN DEVOPS FLAGSHIP PROJECT
Enterprise full-stack digital banking platform deployed with automated 7-stage CI/CD pipelines, modular Terraform IaC, and Kubernetes Helm orchestration.
- 🛠️ 7-Stage Jenkins Pipeline: Automated Git checkout → Linting → Unit Tests → Multi-Stage Docker Build → Trivy Security Scanning → Push to Registry → Automated Helm Deployment.
- ☁️ Terraform AWS Infrastructure: Modular HCL provisioning AWS VPC, public & private subnets, Internet Gateway, NAT Gateway, Application Load Balancer (ALB), and S3 remote state backend with DynamoDB locking.
- ☸️ Kubernetes & Helm Architecture: 11 production Helm charts managing Deployments, ClusterIP & NodePort Services, Ingress routing, ConfigMaps, Secrets, and Persistent Volumes.
- 📊 Observability & SRE: Real-time host and container metric collection using Prometheus and interactive Grafana dashboards.
- Tech Stack: Docker, Kubernetes, Helm, Jenkins, Terraform, AWS, React 19, Node.js, PostgreSQL 16, Redis.
- 🔗 GitHub Repository • Architecture Case Study
MAIN AI/ML & MLOps FLAGSHIP PROJECT
Clinical-grade healthcare AI diagnostic platform powered by autonomous multi-agent reasoning, medical RAG, and containerized microservices.
- 🤖 10 LangGraph Autonomous Agents: Coordinated agent network covering ESI emergency triage, cardiac risk estimation, lab evaluation, drug-drug interaction alerts, and medical literature synthesis.
- ⚡ Production Scale & Performance: 55,000+ lines of Python code, 220+ modules, and 50+ asynchronous FastAPI REST endpoints operating with sub-80ms P95 latency.
- 🐳 Containerized MLOps: Fully Dockerized multi-container setup with Redis caching, ChromaDB vector store, and MedGemma clinical language model.
- 🛡️ Healthcare Compliance: HIPAA-compliant architecture with automated PII de-identification and explainable AI clinical reasoning citations.
- Tech Stack: Python 3.11, FastAPI, LangGraph, MedGemma, ChromaDB, Redis, Docker, PostgreSQL.
- 🔗 GitHub Repository • Architecture Case Study
EDGE AI & COMPUTER VISION
Real-time biometric attendance platform with zero-cloud-dependency edge computer vision inference.
- ⚡ High-Speed Inference: Real-time 30+ FPS face detection and embedding extraction using ONNX Runtime on edge CPU hardware.
- 🛡️ Anti-Spoofing Protection: Texture gradient analysis and blink/liveness detection to prevent 2D photo and screen spoofing.
- 📊 Automated Logging: Automated attendance exports with Redis queue deduplication and SQLite/PostgreSQL persistence.
- Tech Stack: Python, OpenCV, ONNX Runtime, FastAPI, Redis, Streamlit.
- 🔗 Explore in Portfolio
AUTOMATION & DATA PROCESSING
High-throughput asynchronous document extraction, optical character recognition (OCR), and manipulation pipeline.
- ⚡ Batch Processing: Multi-threaded asynchronous parsing of scanned receipts, forms, and enterprise PDFs.
- 🔍 OCR Engine: Tesseract OCR text layer extraction, AES document encryption, and automated watermark stamping.
- Tech Stack: Python, PyPDF2, Tesseract OCR, Streamlit, Docker.
- 🔗 GitHub Repository • Architecture Case Study
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- B.Tech in Computer Science and Engineering (AI & ML)
Vignan's Foundation for Science, Technology and Research (VFSTR) | 2023 – 2027- Academic Score: CGPA: 7.4
- Key Coursework: Operating Systems, Distributed Cloud Computing, Computer Networks, Database Management Systems, System Design, Linux Internals.
- Intermediate (Class XII — MPC)
Sri Chaitanya Junior College | 2021 – 2023 — 9.54 CGPA (95.4%) - Secondary School Certificate (Class X - SSC)
Z.P. High School | 2019 – 2021 — 9.58 CGPA (95.8%)
I am actively interviewing and open to Full-Time Cloud & DevOps Engineer roles and Semester Internships (Immediate Joiner):
- 🌐 Live Portfolio: portfolio-sable-tau-b7ysjwnjns.vercel.app
- 💼 LinkedIn: linkedin.com/in/konda-balaji-rao
- 📧 Work Email: balajikonda9046@gmail.com
- 📞 Phone: +91 83096 36226
- 💻 LeetCode: leetcode.com/u/KBalajiRao
- 📍 Location: Andhra Pradesh, India (Open to Remote & Immediate Relocation)