Back End Developer

AI AXISS INC
Madison, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Madison, United States of America

Tech stack

Java
API
Artificial Intelligence
Amazon Web Services (AWS)
Automation of Tests
Azure
Business Process Model and Notation
Software Quality
Code Review
Continuous Integration
Database Design
Software Debugging
DevOps
Distributed Systems
Hibernate
Spring
JUnit
Machine Learning
Object-Oriented Software Development
Oracle Applications
Performance Tuning
Redis
Mockito
Software Engineering
PL-SQL
SQL Databases
Enterprise Software Applications
GitHub Copilot
React
System Availability
Grafana
Spring-boot
Appian
Backend
Event Driven Architecture
Containerization
AI Platforms
Angular
Git Flow
Kubernetes
Kafka
Front End Software Development
Video Streaming
Software Coding
REST
GPT
Docker
Web Api
Microservices

Job description

The Senior Backend Developer is responsible for designing, developing, and maintaining scalable, high-performance backend systems using Java and Spring technologies bridging software development with operations, building, and maintaining scalable infrastructures (AWS/GCP/on prem), CI/CD pipelines, and backend APIs. This hybrid role focuses on building robust microservices, APIs, and enterprise applications while ensuring performance, security, reliability, and automation while leveraging modern AI-assisted tools and AI capabilities., Key Responsibilities : Design, develop, and maintain scalable backend services and microservices using Java (17+) and Spring Boot., More than 6 years of hand on experience and strong developer as Backend Java with Kafka. Redis and HPC experience

  • Build and optimize RESTful APIs and distributed systems ensuring high availability, performance, and security.
  • Lead system design, architecture decisions, and code reviews to enforce best practices.
  • Integrate AI/ML capabilities and third-party AI services/APIs into backend systems to enable intelligent workflows and automation.
  • Leverage AI-assisted development tools (e.g., GitHub Copilot, ChatGPT) to improve productivity, code quality, and testing efficiency.
  • Develop and maintain infrastructure as code (IaC) and automated testing frameworks using JUnit and Mockito; incorporate intelligent/AI-driven testing techniques where applicable.
  • Collaborate with cross-functional teams including frontend (Angular/React), QA, DevOps, and product teams.
  • Implement and manage CI/CD pipelines, DevOps practices, and containerized deployments.
  • Perform database design and optimization using Oracle, SQL, and PL/SQL.
  • Monitor and support production applications using observability tools; apply intelligent monitoring and anomaly detection techniques.
  • Conduct root cause analysis, debugging, and performance tuning.
  • Ensure adherence to coding standards, security policies, and compliance requirements.
  • Mentor junior developers and promote adoption of modern engineering and AI-enabled practices.
  • Stay updated with emerging technologies in backend engineering, cloud platforms, and AI-driven development.

Requirements

  • 10+ years of experience in Java and Spring (Spring Core, Spring Boot, Hibernate) development.
  • Strong expertise in object-oriented design, microservices architecture, and distributed systems.

Required Skills:

o Java 17+

o Spring Core, Spring Boot, Hibernate

o JUnit, Mockito testing frameworks

o Oracle concepts, SQL, PL/SQL

o Angular 15+

  • Strong experience with DevOps practices, CI/CD pipelines, and branching strategies.
  • Familiarity with AI-assisted development tools and understanding of AI/ML concepts.
  • Hands-on experience with test automation and quality engineering practices.
  • Experience with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).

Other Qualifications (Skills that would be a plus)

  • Experience with React.
  • Familiarity with Kafka (or similar messaging/streaming technologies).
  • Experience with Appian or BPM tools.
  • Knowledge of BPMN tools (RHPAM, IBM BAMOE).
  • Applied understanding of DevOps tools and containerization (Docker Compose).
  • Exposure to AI-driven testing, predictive analytics, or intelligent automation frameworks.
  • Awareness of event-driven architecture and observability tools.
  • Certifications in cloud, DevOps, or AI/ML technologies are a plus.

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