AI-Powered Java Full Stack Engineer
Job in
Phoenix, Maricopa County, Arizona, 85003, USA
Listed on 2026-06-02
Listing for:
Veriipro
Full Time
position Listed on 2026-06-02
Job specializations:
-
Software Development
Cloud Engineer - Software, Software Engineer, Backend Developer, Java Developer
Job Description & How to Apply Below
We are seeking a highly skilled AI-powered Full Stack Engineer with strong expertise in Java, Python, Reactive Programming, and event-driven architectures. The ideal candidate will have hands‑on experience building scalable microservices, streaming systems, and intelligent applications leveraging modern AI and conversational platforms. This role requires strong backend engineering capabilities along with exposure to AI/LLM-driven architectures and cloud-native systems.
Key Responsibilities- Design, develop, and maintain scalable full-stack applications using Java and Python
- Build reactive, high-performance backend systems using Spring Boot and Web Flux
- Develop and optimize event-driven architectures using Apache Kafka
- Work on real-time data streaming pipelines using Apache Flink
- Implement caching and performance optimization using Redis
- Design and develop RESTful APIs and integrate with external systems
- Work with No
SQL (Mongo
DB) and RDBMS (Oracle) databases - Contribute to microservices architecture and cloud-native deployments
- Collaborate with AI/ML and platform teams to integrate LLM and agentic capabilities
- Participate in CI/CD pipeline development and Dev Ops practices
- Ensure system scalability, reliability, and performance
- Strong experience in Java (Spring / Spring Boot)
- 4–5 years of Python backend or data-driven development
- Deep understanding of Reactive Programming (Web Flux or equivalent)
- Hands‑on experience with Apache Kafka for event-driven systems
- Experience with Apache Flink for stream processing
- Proficiency in Redis caching strategies
- Strong knowledge of Mongo
DB and Oracle databases - Expertise in RESTful API design and integration
- Graph
QL knowledge is a plus
- Understanding of Google Dialogflow CX or similar conversational AI frameworks
- Exposure to Large Language Models (LLMs) and prompt engineering
- Familiarity with agentic frameworks such as ADK (Agent Development Kit) or Playbook
- Conceptual knowledge of machine learning fundamentals and model telemetry
- Strong problem-solving and debugging abilities
- Experience with microservices architecture
- Familiarity with CI/CD pipelines and cloud platforms (OCP, Kubernetes, etc.)
- Excellent communication and cross-functional collaboration skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- Experience in banking, fintech, or digital assistant platforms is a plus
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