About this opportunity
Skill lists this Senior Software Engineer, Authentication & Identity opportunity in austin, Texas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Overview
Placement Type:
Temporary
Salary:
$ Hourly
Start Date:
Oct 23, 2026
Duration:
12 months
Join a leading organization in the financial services sector, recognized for its commitment to innovation and delivering secure, seamless digital experiences. Aquent is partnering with this forward-thinking company to find exceptional talent dedicated to shaping the future of technology. Here, you will contribute to a dynamic environment where cutting-edge solutions meet critical business needs, impacting millions of users daily through robust and secure systems.
About the Role
Are you a visionary engineer passionate about shaping the future of digital security and user authentication? We are seeking a highly skilled and independent engineer to join a pivotal team, where you will be instrumental in designing, developing, and supporting cutting-edge enterprise web applications and modern authentication journeys. This is an incredible opportunity to leverage your expertise in building secure, scalable capabilities, including Passwordless Login and Risk Based Authentication. You will play a crucial role in enhancing our digital security posture and user experience, collaborating with diverse stakeholders, and pioneering the practical application of AI-assisted engineering workflows across the software development lifecycle. Your contributions will directly influence the security and efficiency of our platforms, driving innovation and maintaining the highest standards of quality and reliability.
Key Responsibilities
Own the design, development, testing, and support for complex application components and secure authentication capabilities.
Partner with product owners, SCRUM masters, architects, and engineers to decompose features, estimate delivery effort, and meet sprint and release commitments.
Design and implement secure, resilient, user-friendly authentication journeys leveraging risk signals, telemetry, and policy-based decisioning.
Contribute to the evolution of modern identity solutions, including Passwordless Login, FIDO2/WebAuthn/passkey, and Risk Based Authentication.
Build and consume REST APIs, gateway patterns, and reusable services that align with platform principles and architectural standards.
Maintain high standards for automated testing, CI/CD, code quality, security scanning, observability, and release readiness.
Troubleshoot high-stress and time-critical production situations with strong ownership and sound technical judgment.
Mentor less-experienced engineers through code reviews, design discussions, and knowledge sharing.
Utilize AI-assisted engineering tools across day-to-day SDLC activities, including implementation, refactoring, unit testing, regression support, code review preparation, scripting, troubleshooting, and documentation.
Apply agentic and spec-driven development practices by converting design inputs such as API contracts, data models, class structures, and integration details into structured prompts or specifications that support AI-assisted implementation.
Validate AI-generated recommendations, code, tests, and documentation using strong engineering judgment, secure coding practices, and established team quality standards.
Share practical learnings with peers on effective prompt usage, custom instructions, and responsible AI-assisted development patterns.
Required Qualifications
Bachelor's degree 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 frameworks; Angular preferred.
Strong experience developing secure web applications and building or consuming REST APIs.
Experience with Spring Boot, Spring Cloud Gateway or similar gateway patterns, and service-based architectures.
Experience with automated testing frameworks such as JUnit, Karma, Cucumber, BDD, accessibility testing, or similar tools.
Experience with MongoDB, PostgreSQL, or similar data platforms.
Experience with CI/CD technologies, code quality tooling, and secure engineering practices.
Experience with observability and log analysis using tools such as Splunk, BigQuery, Grafana, or similar platforms.
Understanding of OAuth, SAML, JWT, and modern authentication concepts.
Ability to research and apply evolving identity standards and industry practices to scalable solutions.
Hands-on experience or demonstrated practical exposure using GenAI coding assistants such as GitHub Copilot, Claude Code, or similar tools within IDE, CLI, or developer workflow environments.
Ability to use AI assistance for common engineering tasks such as code suggestions, test generation, refactoring support, review preparation, troubleshooting, automation scripts, and documentation while retaining ownership for correctness and quality.
Working familiarity with agentic workflows, spec-driven development, structured prompting, and custom instructions for AI-assisted software delivery.
Ability to validate AI-assisted outputs for correctness, security, maintainability, and alignment with design intent.
Preferred Qualifications
Experience designing or implementing Passwordless Login, FIDO2/WebAuthn/passkeys, or modern authentication journeys.
Experience with Risk Based Authentication concepts including risk scoring, step-up authentication, device signals, behavioral signals, and policy-based access decisions.
Experience deploying containerized applications to GCP, AWS, or similar cloud platforms.
Experience with GitHub Actions, Bamboo, Sonar, Blackduck, Veracode, or similar CI/CD and code security tooling.
Familiarity with NIST identity standards and financial services technology environments.
Performance testing or performance engineering experience.
Experience applying AI-assisted development practices to improve delivery velocity, test coverage, troubleshooting efficiency, documentation quality, or developer productivity.
Exposure to Large Language Models or AI-enabled engineering workflows in enterprise, regulated, or security-sensitive technology environments.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.