Role Description As a Staff Software Engineer, you will help make SiriusXM’s massive content catalog easily discoverable across automotive and mobile platforms. You’ll work on the core search infrastructure that powers how millions of users find content every day. In this role, you’ll: - Design, scale, and evolve distributed search systems that retrieve high-quality results at scale. - Drive architectural decisions and own complex, business-critical components. - Establish best practices as the team and platform grow. - Explore new ML models and re-architect search services to improve scalability, reliability, and cost efficiency. - Collaborate closely with content services teams, product partners, ML/science teams, and downstream client applications to deliver cutting-edge search experiences. Qualifications - 7+ years of professional software engineering experience building large-scale backend systems in Java. - 3+ years of experience with Python. - Deep experience with search frameworks, metadata indexing, and retrieval systems. - Proven experience leading complex, cross-functional technical initiatives. - Expert-level experience with AWS, including deploying applications using services such as EC2, Lambda, S3, DynamoDB, CloudWatch, ElastiCache, and IAM. - Strong foundation in object-oriented design, system design, and design patterns. - Proven ability to make sound architectural trade-offs while maintaining long-term extensibility. - Comfort working across system boundaries (infrastructure, ML, and adjacent service domains). - Ability to handle multiple tasks in a fast-paced environment. - Excellent interpersonal and communication skills. - Willingness to take initiative and to follow through on projects. - Excellent time management skills, with the ability to prioritize and multitask, and work under shifting deadlines in a fast-paced environment. - Must have legal right to work in the U.S. Requirements - Compensation range: $101,500 to $195,000, depending on skills, qualifications, and experience. - This role might be eligible for discretionary short-term and long-term incentives. Benefits - Work environment that fosters mutual respect, professionalism, and cooperation. - Equal opportunity employer that does not discriminate on the basis of various characteristics protected by applicable laws.

Role Description Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. - Design, develop, and own complex, scalable user interfaces using React and modern frontend technologies - Lead the implementation of UI features with a strong focus on performance, reliability, and maintainability - Build reusable, modular UI components and frontend architectures that support long‑term scalability - Integrate AI‑assisted development practices to improve code quality, development efficiency, and delivery speed - Apply AI‑based tools for code generation, refactoring, debugging, testing, and UI optimization where appropriate - Ensure high standards of code quality through clean design, unit and integration testing, documentation, and code reviews - Integrate frontend applications with backend services and APIs to deliver seamless end‑to‑end functionality - Troubleshoot, debug, and resolve complex UI issues across development, testing, and production environments - Optimize application performance, rendering behavior, and state management in large‑scale React applications - Contribute to frontend modernization initiatives, including improving UI architecture, tooling, and engineering practices - Provide onshore support during US business hours to triage and resolve UI‑related production and deployment issues - Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI. Qualifications - Bachelor's degree in Computer Science, Engineering, or equivalent practical experience - 5+ years of professional experience in building full-stack applications - 5+ years of backend development experience using Java - 3+ years of experience with React, modern frontend technologies - 3+ years of experience designing and consuming RESTful or GraphQL APIs Requirements - Backend development experience, Node.js, Python, or similar server-side technologies - Strong hands-on experience with AWS cloud services, including application deployment and troubleshooting - Proficiency in writing clean, testable, and maintainable code across frontend and backend layers - Experience using AI-assisted development tools for coding, testing, or developer productivity - Familiarity with CI/CD pipelines, version control systems, and agile development practices - Strong debugging and problem-solving skills, including production issue resolution - Knowledge of security best practices for web applications and cloud environments Benefits - Comprehensive benefits package - Incentive and recognition programs - Equity stock purchase - 401k contribution (all benefits are subject to eligibility requirements)

• Lead the design and development of quantitative data engineering models, including algorithms, data pipelines, and data processing systems, to support business requirements. • Develop and maintain data processing pipelines to ingest, clean, transform, and aggregate large volumes of data from various sources, ensuring data quality and reliability. • Design and implement algorithms for data analysis, machine learning, and statistical modeling, using techniques such as regression analysis, clustering, and predictive modeling. • Identify and implement optimizations to improve the performance and efficiency of data processing and modeling algorithms, considering factors like scalability and resource utilization. • Create visualizations of data and model outputs to communicate insights and findings to stakeholders. • Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data used in models and analyses. • Evaluate the performance of data engineering models using metrics and validation techniques, and iterate on models to improve their accuracy and effectiveness. • Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop models, and deliver insights that drive business decisions. • Document the design, implementation, and evaluation of data engineering models, including assumptions, methodologies, and results, to ensure reproducibility and transparency. • Stay updated with the latest trends, tools, and technologies in quantitative data engineering and data science, and continuously improve your skills and knowledge.

• Own day-to-day operations of the Burp Suite Enterprise DAST program: scan scheduling, agent and Linux infrastructure health, scan tuning, and result triage across multiple federal application environments. • Configure and troubleshoot authenticated scans against modern web applications and APIs, including recorded login sequences (via the official Burp recorder Chrome extension), session-handling rules, and macro-based re-authentication. • Diagnose and resolve Burp Enterprise scan failures end to end: consecutive audit-item failures, skipped insertion points, timeouts, session invalidation, and authentication state loss. • Extend Burp Suite Professional with custom extensions (Python/Java/Montoya API) to automate repetitive manual verification, custom authentication flows, and findings validation for the bug bounty program. • Design and implement authenticated scan workflows that survive multi-factor authentication, including SMS one-time passwords, TOTP tokens, hardware dongles, PIV and smart card client-certificate authentication, and SSO federation. • Administer the AppSec team’s own Linux infrastructure in AWS (currently EC2 with containerized Burp Enterprise components) and contribute to the migration to on-premise OpenShift. • Convert legacy Python and shell tooling left behind by previous engineers into Ansible roles and playbooks; manage YAML, Dockerfiles, and Kubernetes manifests as code. • Integrate AppSec tooling into GitHub Actions workflows alongside Dependabot SCA, including the appropriate use of workflow_dispatch versus workflow_call patterns and reusable workflows. • Provide secondary support to the broader AppSec toolset: Veracode SAST, Contrast IAST for interactive scanning and runtime security testing, GitHub Advanced Security workflows, and the HackerOne bug bounty program (validating reported findings with Burp Suite Professional).