Java Full Stack
- Tanisha Systems, Inc.
3 Days Ago
NA
W2
Remote
6-15 Years
Required Skills: Azure, AWS, GCP, Docker, Kubernetes, Kafka, Event Hub, Java, Spring Boot, Microservices
Job Description
Key Responsibilities
Core Development
Core Development
- Design, develop, and maintain enterprise-grade applications using Java and Spring Boot / Microservices architecture
- Build scalable, secure, and high-performance REST/GraphQL APIs
- Ensure code quality through unit testing, code reviews, and adherence to best practices
Cloud & Platform Engineering
- Develop and deploy applications on cloud platforms (Azure / AWS)
- Work with containerization and orchestration technologies such as Docker and Kubernetes
- Build CI/CD pipelines using tools like Jenkins, GitHub Actions, Azure DevOps
- Implement event-driven architectures using Kafka / Event Hub
AI & Automation Enablement
- Leverage enterprise AI tools (e.g., GitHub Copilot, M365 Copilot) to improve development productivity
- Contribute to integration of AI/ML or GenAI capabilities into applications (e.g., APIs, automation, decisioning systems)
- Demonstrate understanding of RAG pipelines, LLM integration, or AI-driven workflows (preferred exposure)
Engineering Excellence
- Troubleshoot production issues and ensure system stability
- Mentor junior developers and contribute to architectural discussions
- Stay updated with emerging technologies and drive continuous improvement
Required Qualifications
- 6–10 years of experience in Java backend development
- Strong expertise in:
- Java, Spring Boot, Microservices
- REST APIs and distributed systems
- SQL/NoSQL databases (Oracle, MongoDB, Cassandra, etc.)
- Hands-on experience with:
- Cloud platforms (Azure / AWS / GCP)
- Containerization (Docker, Kubernetes)
- CI/CD and DevOps practices
- Experience with messaging/event streaming (Kafka / Event Hub)
- Solid understanding of system design, scalability, and performance tuning
Preferred Qualifications
- Exposure to AI/ML / Generative AI concepts (LLMs, RAG, prompt engineering)
- Experience with tools like:
- LangChain, Vector Databases, AI APIs
- Familiarity with Python or data processing frameworks (PySpark)
- Experience in domain-driven design (DDD) and event-driven architecture
- Prior experience in healthcare or regulated domains
AI Expectations (Enterprise Enablement)
- Demonstrate consistent usage of enterprise-approved AI tools for:
- Code generation and optimization
- Documentation and debugging
- Apply AI capabilities to improve delivery speed, quality, and innovation
- Continuously learn and adopt new AI advancements in software engineering
Nice-to-Have Differentiators
- Experience modernizing legacy/mainframe systems to microservices
- Exposure to agentic AI / autonomous workflows
- Experience building platform-level or reusable services
