AquSag Technologies is looking for a Senior Java Full Stack Developer with deep backend expertise, modern frontend skills, and hands-on experience with cloud platforms and AI/GenAI integration. You will work directly inside the client's delivery pipeline, using their tools and processes. Strong ownership, production experience, and the ability to hit the ground running are essential.
Required Experience
- 8 to 12 years of hands-on Java full stack development experience
- Production delivery on enterprise-grade applications at scale
- Experience working on client-facing programs in financial services, healthcare, or enterprise SaaS preferred
- Prior experience in a contractual or staff augmentation model is a plus
Backend Skills
- Java 8/11/14/17/19, Kotlin, J2EE - strong fundamentals across modern versions
- Spring Boot, Spring MVC, Spring WebFlux, Spring Data JPA, Spring Security, Spring Batch, Spring AI
- Microservices architecture, RESTful APIs, GraphQL, SOAP
- Hibernate, JPA, ORM optimisation, connection pooling
- Apache Kafka, RabbitMQ, ActiveMQ, JMS for event-driven systems
- OAuth 2.0, JWT, HTTPS/TLS, OWASP, GDPR compliance
- Maven, Gradle, SonarQube, build automation
- Application servers: Apache Tomcat, JBoss, WebSphere, WebLogic, GlassFish
Frontend Skills
- Angular (12, 15+, NgRx, RxJS, Angular CLI, lazy loading)
- React (functional components, hooks, Redux)
- JavaScript, TypeScript, HTML5, CSS3, Bootstrap, Material-UI, jQuery, Ajax
- Single-page application development, responsive design, cross-browser testing
Cloud & DevOps
- AWS: EC2, S3, RDS, Lambda, API Gateway, IAM, ECS, EKS, CodeBuild, Bedrock, CloudWatch
- Azure: Azure Functions, Blob Storage, Azure AD, Azure OpenAI, Azure API Management
- GCP: Vertex AI, GCP-native configurations
- Docker, Kubernetes, Jenkins, GitHub Actions, GitLab CI/CD
- Infrastructure as Code, CloudFormation, serverless architectures
AI & GenAI Integration
- LLM integration using Spring AI, OpenAI, Azure OpenAI modules
- RAG (Retrieval-Augmented Generation) pipeline design and implementation
- MCP Server architecture for LLM-backend integration
- Vector databases: PGVector, PGVecto for semantic search
- Prompt engineering, AI-assisted code generation (GitHub Copilot preferred)
- AWS Bedrock, Oracle AI, GCP Vertex AI hands-on exposure
Databases
- PostgreSQL, Oracle, SQL Server, MySQL, H2
- MongoDB, Cassandra, NoSQL at scale
- Schema design, indexing, caching, query optimisation
- PL/SQL, stored procedures, transactional performance
Testing & Quality
- JUnit, Mockito, MockMvc, Cucumber (BDD), Selenium, Apache JMeter
- Jest, Karma, Jasmine for frontend testing
- TDD practices, code coverage, SonarQube gates
- Monitoring: Prometheus, Grafana, ELK Stack, Log4j, SLF4J
Certifications - Strongly Preferred
Candidates holding one or more of the following certifications will be prioritised:
- AWS Certified Solutions Architect - Associate or Professional
- Microsoft Certified: Azure Solutions Architect Expert
- AWS Certified AI Practitioner Foundational
- Google Cloud Professional Cloud Architect
- Any active cloud or AI certification from AWS, Azure, or GCP
What We Are Looking For
Immediate joiners or candidates with a notice period of 15 days or less are strongly preferred. This is a client-facing role. You will work inside the client's tools and PM structure from day one. Strong communication, ownership, and the ability to deliver without hand-holding are non-negotiable.
Engagement Details
Location: Remote / Pan India
Engagement type: Contract (with possibility of extension or conversion)
Working hours: Client timezone aligned
Vetting process: Internal screening followed by client interview