Backend:- Strong fundamentals - Solid understanding of core concepts (data structures, OOP, basic system design principles) relevant to our stack. - Problem-solving ability - Can break down problems logically and demonstrate clear thinking, even if they don’t reach the perfect solution. - Basic hands-on experience - Familiarity with Java/Spring Boot, REST APIs, OpenAPI, and Git through projects, internships, or coursework. - Willingness to learn & good attitude - Open to feedback, proactive, and shows genuine interest in growing rather than just completing tasks.DevOps:- Foundational Systems (Linux & AWS) - Comfortable with the Linux CLI (permissions, bash) and a conceptual grasp of AWS basics (EC2, S3, IAM). - Container Orchestration (Kubernetes/Docker) - Understanding of containerization and the ability to define basic K8s objects (Pods, Services). Familiarity with kubectl. - CI/CD & GitOps Philosophy - A high-level understanding of how code gets built and deployed automatically, and a strong grip on Git (branching, merging, PRs). - The "DevOps" Mindset - A proactive approach to troubleshooting and a "learning-first" attitude specifically the ability to research an error message before asking for help.Frontend:- TypeScript/ReactJS fundamentals & clean component development - Understand React and TypeScript basics, build reusable and maintainable components, use proper typing, naming conventions. - Storybook usage & component documentation -Be able to create and maintain Storybook stories for UI components. - Frontend testing mindset - Learn how to write basic tests for components and user interactions, including Storybook testing and frontend unit/integration tests. - Build tools & monorepo awareness - Understand the basics of Vite, bundling, package structure, and how to work inside a monorepo/monospace setup, including shared UI packages and dependencies.AI :- AI Agent Development with Spring AI & MCP - Build AI agents using Java Spring Boot with Spring AI and Spring AI MCP, including creating MCP servers, defining tools (skills), and wiring agent workflows - RAG & Embeddings Integration - Implement a basic RAG setup using embeddings (store + retrieve) and integrate it into agents for contextual responses - Custom Agent Design & Skill Integration - Develop simple custom agents that can call APIs, process user input, and orchestrate tasks using modular skills - Experimentation & Feature Improvement - Collaborate on experimenting with new agent capabilities, testing ideas, and improving usability and performance of AI-driven features