Java Full Stack + AI Developer
Requirements at a glance
Java Full Stack + AI Developer at Jadeglobal is a role based in Pune, Maharashtra. It does not mention visa sponsorship. Key skills include Node.js. Applications are submitted through Workday.
- Visa sponsorship
- Not mentioned in the posting
- Application platform
- Workday
Skills in this posting
- Node.js
- JavaScript
- TypeScript
- Python
- Java
- SQL
- React
- Spring
- AWS
- Azure
- Google Cloud
- Kubernetes
- Docker
- Git
- PostgreSQL
- MySQL
- MongoDB
- Kafka
- REST APIs
- Machine learning
- Generative AI
- Agile
Highlighted skills appear in the posting's requirements.
Extracted automatically from the job description. Confirm details in the full posting below.
Key Responsibilities
Design, develop, and maintain backend services using Java, Spring Framework, Spring Boot, and Hibernate.
Build and consume Microservices architectures with secure, scalable, and reliable communication.
Develop responsive and user-friendly React-based frontend interfaces.
Implement server-side components and APIs using Node.js where required.
Integrate applications with cloud platforms (AWS/Azure/GCP) for deployment, storage, and scalability.
Experience in building and integrating AI agents using frameworks like LangChain / LangGraph, OpenAI Assistants,
HuggingFace.
Collaborate closely with cross-functional teams (Product, QA, DevOps, UI/UX).
Participate in code reviews, performance optimization, troubleshooting, and debugging.
Maintain coding standards, documentation, and ensure secure coding practices.
Support CI/CD pipelines, containerization, and DevOps activities for smooth deployments.
Required Skills & Qualifications
5–8 years of hands-on experience in full stack development.
Strong backend development experience with:
Java, Spring, Spring Boot
Hibernate/JPA
RESTful APIs
Microservices architecture
Frontend development experience using React, JavaScript, TypeScript, HTML5, CSS3.
Experience with Node.js for backend or middleware services.
Knowledge of Cloud technologies (AWS, Azure, or GCP)—deployments, storage, compute, container services, etc.
Strong communication and collaboration skills.
Ability to work independently and take end-to-end ownership.
Working knowledge of Python for interacting with core AI/ML services or models.
Solid understanding of LLMs, RAG, embeddings, and vector databases.
Practical experience building AI agent pipelines.
Knowledge of prompt engineering and model fine-tuning techniques.
Familiarity with:
Git, Maven/Gradle
CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.)
Docker/Kubernetes basics
SQL/NoSQL databases (MySQL, PostgreSQL, MongoDB)
Preferred Qualifications
Experience working in Agile/Scrum environments.
Exposure to messaging systems like Kafka or RabbitMQ.
Knowledge of security standards (OAuth2, JWT, SSL).
Experience with monitoring tools (Prometheus, ELK, Grafana).