Senior Java Developer (AI-Augmented Engineering)

Senior Java Developer (AI-Augmented Engineering)

Irving TX / Basking Ridge, NJ (Hybrid)

Face2Face Interview

Long Term Contract

JD:

We are seeking a forward-thinking, highly skilled Senior Java Developer with 5 7 years of experience to join our engineering team.

In this role, you will design, build, and maintain robust, scalable enterprise applications while championing the next generation of software development by deeply integrating AI collaboration tools into your daily workflow.

The ideal candidate is an expert in the Java ecosystem who treats AI assistants-such as GitHub Copilot, Claude, and Gemini-as force multipliers. You should possess strong prompt engineering skills, enabling you to accelerate development velocity, optimize code quality, automate testing, and solve complex architectural challenges efficiently.

Key Responsibilities

Core Java Development

Design, develop, and maintain high-performance, scalable, and secure microservices and enterprise applications using Java 17/21 and the Spring Boot framework.
AI-Assisted Engineering

Seamlessly integrate AI coding assistants (GitHub Copilot, Claude, Gemini) into the Software Development Life Cycle (SDLC) to write clean code, refactor legacy systems, and generate technical documentation.
Advanced Prompt Engineering

Formulate, test, and refine advanced prompts (system prompts, few-shot prompting, and chain-of-thought/chained prompting) to generate high-context, syntactically correct, and secure code from Large Language Models (LLMs).
Code Quality & Reviews

Review both human-written and AI-generated code to ensure adherence to design patterns, security standards, performance benchmarks, and organizational best practices.
Testing & Automation

Leverage AI tools to rapidly generate robust unit, integration, and regression test suites using JUnit, Mockito, and related frameworks to improve code coverage and reliability.
Troubleshooting & Optimization

Utilize LLMs to accelerate root-cause analysis, interpret complex stack traces, identify performance bottlenecks, and optimize application performance.
Continuous Learning

Stay current with evolving AI technologies and modern software engineering practices, while sharing prompt libraries, best practices, and technical knowledge across the development team.
Required Skills & Qualifications

Java & Technical Architecture

Experience: 5 7 years of professional software development experience using Java 11+ (Java 17 or higher preferred).
Frameworks: Extensive hands-on experience with Spring Boot, Spring Cloud, and Hibernate/JPA.
Microservices: Strong understanding of microservices architecture, RESTful API design, and event-driven architectures.
Databases: Experience with relational databases such as PostgreSQL and MySQL, along with NoSQL databases including MongoDB and Redis.
DevOps & CI/CD: Hands-on experience with Git, Docker, Kubernetes, and CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
AI & Prompt Engineering

AI Tool Expertise

Daily hands-on experience using GitHub Copilot (or Copilot Chat), Claude, and Gemini to accelerate software development.
Prompt Engineering

Proven ability to craft effective prompts by providing appropriate context and applying techniques such as:
System prompting
Few-shot prompting
Chained prompting
Context engineering
Hallucination reduction strategies
AI Validation & Security

Strong ability to critically evaluate AI-generated code for:
Security vulnerabilities (OWASP Top 10)
Performance issues
Licensing risks
Code quality and maintainability
Soft Skills

Critical Thinking: Ability to question, validate, and improve AI-generated outputs rather than accepting them blindly.
Adaptability: Growth mindset with a passion for learning emerging AI tools and software development practices.
Collaboration & Communication: Strong communication skills with the ability to effectively collaborate with both engineering teams and AI assistants.
Preferred Qualifications

Experience building or integrating custom AI plugins, internal developer tools, or AI-powered engineering solutions.
Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Active contributions to open-source projects or a portfolio demonstrating innovative use of AI in software development.