Inherent Technologies
Java Full Stack Developer
Washington, District of Columbia · Contract
Sponsorship not specifiedDetected 27 days ago
JavaReactAngularSpringDistributed SystemsFull-Stack DevelopmentGitNoSQLRedisAzureCloud PlatformsDockerKubernetesCI/CDKafkaData AnalysisLLMsAgentic AIAgileLoad BalancingMentoring
About the role
- 3+ Experience working with Microservices and Event driven architecture like Kafka
- Strong knowledge in performance, scalability, distributed architecture, and engineering best practices
Responsibilities
- Understand and implement CI/CD deployment pipelines with JPAC/Github Actions.
- Understand Product / Project / Consumer priorities and follow Agile methodologies to deliver features within time.
- Creation/involvement in documented designs following agreed to design patterns and standards.
- Support the QE team during testing via defect fixes, code deployment, clarifications
- Fully encourage and facilitate high quality code through of support QE team efforts including but not limited to mentoring, assistance, and writing/executing automation tests as needed.
Requirements
- 9+ years of experience in large scale distributed system development including hands on operational experience
- 5+ Hands on experience with Java, Spring boot, Kafka, AngularJS/ReactJS, NoSQL Database, Redis, Docker/Kubernetes, GitHub
- 1+ experience with AI development using Agentic AI, Chatbot and Gen AI
- Proven experience with full development life cycle for large-scale software products including extensive experience with service-oriented architectures, design patterns and web services
- In-depth knowledge of system programming, Deep understanding of system performance tradeoffs, load balancing, and engineering for high availability
- Perform Coding and unit testing independently and assist/mentor his team members whenever required.
Skills
- Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows.
- 2+ experience on Cloud environment and architectures, preferably Azure
- Applied Productivity: Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows.
Benefits
- Continuous Learning: Stay current with evolving AI capabilities and features, and apply them to improve delivery quality and velocity.
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