Software Engineer, Identity & Security Platforms

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Software Engineer, Identity & Security Platforms

• Location: Austin, Texas 78758
• Work model: On-site
• Posted 2 weeks ago
• Job ID: JPC - 210673

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Job Description

Software Engineer, Identity & Security Platforms

Location: Austin, TX (Onsite 4 days/week from day one)

Compensation: Up to $65/hour W2 (+$5/hour referral available)

About the Role

Join a high-impact Enterprise Middleware and Online Security Technology team as a Full Stack Java Software Engineer specializing in Secure Authentication and Identity. You'll architect and deliver secure, scalable authentication features, champion AI-assisted engineering, and shape the future of enterprise web applications and modern authentication journeys. Collaborate directly with cross-functional experts in security, fraud, risk, and architecture, while leveraging cutting-edge AI tools to accelerate software delivery and innovation.

Responsibilities

• Lead design, development, testing, and support for secure, complex enterprise application components and modern authentication solutions.
• Partner with product owners, SCRUM masters, architects, and engineers to break down features, estimate delivery, and meet sprint goals.
• Build resilient, user-friendly authentication journeys using risk signals, telemetry, and policy-based decisions.
• Design and integrate Passwordless Login, FIDO2/WebAuthn/passkey, Risk-Based Authentication, and advanced identity solutions.
• Develop and consume REST APIs, implement gateway patterns, and create reusable services following architectural standards.
• Uphold rigorous standards for automated testing, CI/CD, code quality, security scanning, observability, and release readiness.
• Troubleshoot high-priority production issues with strong ownership and sound engineering judgment.
• Mentor and uplift team members through code reviews, design discussions, and knowledge sharing.
• Apply AI-assisted engineering tools throughout the SDLC-implementation, refactoring, unit testing, scripting, troubleshooting, and documentation.
• Convert design inputs into structured prompts for agentic, spec-driven AI-assisted development.
• Validate and refine AI-generated code, tests, and documentation, maintaining secure coding practices.
• Share insights and best practices around AI prompt engineering and responsible AI-assisted software development.

Required Skills and Experience

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5+ years developing enterprise applications with Java, JavaScript, and modern frameworks (Angular preferred).
• Strong experience in secure web application development and REST API integration.
• Proficiency with Spring Boot, Spring Cloud Gateway, and service-based architectures.
• Skilled with automated testing tools such as JUnit, Karma, or Cucumber.
• Experience with MongoDB, PostgreSQL, or similar databases.
• Hands-on with CI/CD, code quality, security tooling, and observability (Splunk, BigQuery, Grafana).
• Understanding of OAuth, SAML, JWT, and modern authentication protocols.
• Practical exposure to GenAI coding assistants (e.g., GitHub Copilot) and AI-assisted engineering workflows.
• Ability to validate AI outputs for correctness, security, and alignment with design intent.

Preferred Skills

• Experience with Passwordless Login, FIDO2/WebAuthn/passkeys, or modern authentication implementations.
• Knowledge of Risk Based Authentication, risk scoring, and policy-driven access.
• Familiarity with GCP, AWS, or cloud-based container deployment.
• Experience with GitHub Actions, Bamboo, Sonar, Blackduck, Veracode, or similar tooling.
• Understanding of NIST identity standards and financial services technology.
• Performance testing or engineering experience.
• Experience leveraging AI/LLM workflows in enterprise or regulated environments.

Benefits

• Competitive hourly rate with referral bonus.
• Work alongside top talent in a collaborative, innovative environment.
• Gain hands-on experience with the latest in AI-assisted software engineering.
• Career advancement opportunities in enterprise security and identity technology.
• Influence technology strategy and mentor the next generation of engineers.

How to Apply

Ready to shape the future of secure enterprise authentication using leading AI-driven engineering practices? Submit your resume today to join our Austin-based team and accelerate your career in security technology.

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Job details

Job ID JPC - 210673

Location Austin, Texas, United States

Work Model On-site

Job Type Referral Fee

Posted September 30, 2026

Skills Location: Austin TX (Must be able to work onsite 4 days per week from day one)Rates are Below - PLEASE do not submit over these rates listedIf a referral then we can pay the candidate up to $65/hour W2 with a $5/hour referralJob Details: Software Engineer - Full St this role is for an engineer who can own complex features contribute to design decisions and deliver secure scalable authentication capabilities The successful candidate will help build and support enterprise web applications and modern authentication journeys This role requires strong engineering judgment production support discipline and the ability to partner with product security Fraud Risk Architecture and platform stakeholders It also requires practical use of AI-assisted engineering workflows across the software development lifecycle Key Responsibilities• Own 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 commitments• Design and implement secure resilient user-friendly authentication journeys using risk signals telemetry and policy-based decisioning• Contribute to Passwordless Login FIDO2/WebAuthn/passkey Risk Based Authentication and modern identity solutions• 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 time-critical production situations with strong ownership and sound technical judgment• Mentor less-experienced engineers through code reviews design discussions and knowledge sharing• Use AI-assisted engineering tools across SDLC activities including implementation refactoring Unit Testing scripting troubleshooting and documentation• Apply agentic and spec-driven development practices by converting design inputs into structured prompts for AI-assisted implementation• Validate AI-generated recommendations code tests

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