Bhavani Patel
AI/ML Engineer | Expert in LLMs, RAG, and Generative AI | Cloud-Native Solutions | AWS, PyTorch, TensorFlow | MLOps | Responsible AI Advocate | Scaling Enterprise AI Solutions
- Role
- Java Full Stack Developer at Meta
- Location
- San Francisco, CA, US
- LinkedIn followers
- 500 followers
About Bhavani Patel
Machine Learning Engineer with 4+ years of experience specializing in LLMs, Generative…
Experience
Java Full Stack Developer
Jun 2024 — Present · San Francisco, CA, US
Developed and deployed scalable, distributed microservices architecture using Java 17, Spring Boot, and Spring WebFlux,capable of handling high concurrent user loads while consistently maintaining sub-200ms API response times throughnon-blocking, reactive programming.• Created modular, component-based web applications using Angular 14, HTML5, CSS3, and TypeScript, incorporating ARIA attributes and semantic elements to ensure WCAG 2.1 Level AA compliance, cross-device responsiveness, and enhanced accessibility.• Implemented enterprise-grade authentication and authorization using Spring Security, OAuth 2.0, and JWT, supporting role-based access control (RBAC), session management, and SSO integration for both web and mobile clients across secure channels.• Managed cloud-native deployments on Oracle Cloud Infrastructure (OCI) using Docker containers, orchestrated via Kubernetes clusters, and provisioned infrastructure as code (IaC) using Terraform, cutting provisioning time and reducing manual errors by over 60%.• Integrated Hibernate ORM and JPA for complex data persistence, handled lazy/eager fetching strategies, optimized entity relationships, and collaborated with DBAs to design and implement normalized Oracle DB schemas, materialized views, and indexed stored procedures.• Developed comprehensive test automation suites using REST Assured for API testing, Postman for contract validation, and JUnit for unit testing, enforcing 80%+ code coverage and establishing regression baselines in CI workflows for every build.• Designed and maintained end-to-end CI/CD pipelines using GitHub Actions, integrated SonarQube for static code analysis, and applied Jacoco for module-wise code coverage reporting, ensuring code quality gates and continuous improvement across sprints.
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