Java Software Engineer - Hybrid

Smart IMS•Austin, TX

5d•Hybrid

About The Position

As a Java Software Engineer, you will design, develop, and support secure, scalable enterprise applications with a focus on authentication, identity, and web security solutions. You will work closely with product, security, architecture, and engineering teams to deliver modern authentication capabilities while leveraging AI-assisted development practices to improve software quality, testing, troubleshooting, and delivery efficiency.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
5+ years of experience developing enterprise applications using Java, JavaScript, and modern web technologies.
Strong experience with Spring Boot, Spring Cloud Gateway, REST APIs, and service-oriented architectures.
Experience building secure web applications and implementing authentication and authorization solutions.
Knowledge of OAuth, SAML, JWT, and modern identity management concepts.
Experience with MongoDB, PostgreSQL, or similar database technologies.
Hands-on experience with CI/CD pipelines, automated testing frameworks, secure development practices, and code quality tools.
Experience using observability and monitoring tools such as Splunk, Grafana, BigQuery, or similar platforms.
Practical experience with AI-assisted development tools such as GitHub Copilot, Claude Code, or similar technologies.

Nice To Haves

Experience with cloud platforms, containerized deployments, Passwordless Authentication, Risk-Based Authentication, FIDO2/WebAuthn, and identity security solutions is highly preferred.

Responsibilities

Design, develop, test, and support enterprise application components and secure authentication solutions.
Build and maintain modern authentication capabilities including Passwordless Login, FIDO2/WebAuthn, passkeys, and Risk-Based Authentication.
Develop and consume REST APIs, reusable services, and gateway-based architectures.
Collaborate with architects, product owners, Scrum teams, and stakeholders to define and deliver platform capabilities.
Maintain high standards for automated testing, CI/CD, observability, code quality, and release readiness.
Troubleshoot complex production issues and provide operational support for critical applications.
Mentor team members through code reviews, design discussions, and technical guidance.
Utilize AI-assisted development tools to support coding, testing, debugging, documentation, and automation activities.
Apply secure coding practices and validate AI-generated code, tests, and recommendations.
Research and adopt emerging authentication, identity, and software engineering best practices.