Description

Skills Needed: AI Engineer, Java

Must-have skills & experience:
3-6 years of hands-on experience building full stack applications using Java and the Spring Boot framework (or equivalent) in a production environment.
Experience working in a large enterprise or complex organization (multiple teams, services, stakeholders).
Solid backend development skills: Java 8+, Spring Boot, RESTful APIs, data access (JPA/Hibernate), relational databases (e.g., PostgreSQL, MySQL) and familiarity with NoSQL as a plus.
Frontend experience: delivered client side UI using frameworks like React (strongly preferred) or Angular/Vue, with good working knowledge of HTML5, CSS, JavaScript/TypeScript.
Hands-on experience with modern AI workflows: developing agents, working with LLMs, integrating AI capabilities into applications (e.g., prompt engineering, model orchestration)
Experience taking an AI-centric systems into production: build, deploy, monitor, troubleshoot live services, handle performance, scalability, stability.
Familiarity with enterprise-grade practices: version control (Git), CI/CD pipelines, automated testing (unit, integration), code reviews, agile methodologies.
Experience building event-driven or streaming systems (Kafka, Reactor, etc.).
Experience with containerization and orchestration (Docker, Kubernetes) or cloud deployments.
Hands-on developing front-end/back-end interactions in the context of AI workflows (UI for model output, integrations).
Understanding of architecture in enterprise settings: microservices or modular architectures, ability to work within a larger ecosystem of services, dependencies, security and operations concerns.
Excellent problem-solving skills, able to diagnose issues in production systems and propose solutions.
Good communication skills: work across teams (DevOps, QA, product, architecture) and clearly articulate technical trade-offs

Key Skills

Education

Any Graduate