Summer Internship Technology

Open 44d

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.

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 Kubernetes 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, pull requests).
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.

TypeScript/ReactJS fundamentals & clean component development
Understand React and TypeScript basics, build reusable and maintainable components, use proper typing, and 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 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.

See also