Staff Engineer, AI Native
Sony · San Diego
- Location
- San Diego
- Salary
- $220,000–$240,000
- Experience
- 8+ years
- Funding
- ~$136.6B
- Posted
- Oct 26, 2026
Sony is hiring a Staff Engineer, AI Native based in San Diego. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.
Apply directly at SonyRole details
Join the Sony Engagement Platform Services (SEPS) Team, where innovation meets collaboration in the dynamic world of digital engagement. At SEPS, we are building the next-generation platform that powers how fans connect with the content—and the creators—they love. Our mission is to unlock meaningful, data-driven engagement across Sony’s entertainment ecosystem, from games and anime to music, film, and live experiences—empowering both internal teams and external partners to build at scale. Our mission is to create a world-class engagement platform that not only enhances existing revenue streams but also drives new opportunities through a robust ecosystem of partners and creators. By decoupling application development from platform services, we empower our teams to deliver exceptional solutions with agility and efficiency. If you are passionate about shaping the future of digital engagement and want to be part of a vibrant community that values creativity and collaboration, we invite you to explore the exciting opportunities within our team. Together, we will shape the future of fan experiences and define the foundation for what’s possible in the realm of engagement. To learn more visit: www.sony.com/en/SonyInfo/technology/stories/entries/sep_introduction/ POSITION SUMMARY SEPS is seeking a highly skilled and experienced AI-Native Staff Software Engineer to support the development of the applications that power the Sony Engagement Platform. In this role, you will design and build secure, scalable, and high-performing solutions that deliver exceptional user experiences across Sony's global ecosystem. As a Staff Engineer, you will contribute to both front-end and back-end systems, playing a hands-on role in architecture, implementation, and technical leadership. You will operate as part of an AI-native tiny team, directing and governing AI agents across the full delivery lifecycle. You’ll collaborate closely with product managers, designers, and other engineering teams to build robust, maintainable applications. This is a dynamic opportunity for individuals who thrive in a fast-paced, innovation-driven environment and are passionate about solving complex challenges with clean, thoughtful code. JOB RESPONSIBILITIES Architect, design and develop RESTful API Endpoints, ensuring high performance, scalability and maintainability. Collaborate closely with front-end engineers to build dynamic, responsive, and user-centric web applications that deliver seamless user experiences. Define robust data models and database schemas, and manage relational or NoSQL databases with a strong emphasis on data integrity and performance optimization. Direct and govern AI coding agents across the delivery lifecycle, setting context, reviewing agent-generated output, and enforcing SEPS delivery standards at every gate. Design and maintain agent workflows using agentic coding tools (Claude Code, Cursor, Copilot) and the AI- native development framework, ensuring structured, auditable, and high-quality delivery. Configure and maintain prompt engineering patterns, structured output schemas, with rules and guardrails to align agent behavior with SEPS platform standards. Trace, debug, and triage agent tool calls, prompt failures, and unexpected outputs, maintaining visibility into AI-assisted delivery at every stage. Create and maintain clear, comprehensive documentation for application architecture, design, configuration, and ongoing maintenance. Provide accurate task estimations and delivery timelines, contributing to effective sprint planning and execution. Participate in the on-call rotation, responding promptly to production issues and ensuring system stability and uptime. Mentor and support junior engineers, fostering a culture of AI-native ways of working, learning, and continuous improvement. Honesty, trustworthiness and ethical conduct are material requirements for the responsibilities outlined above QUALIFICATIONS FOR POSITION Your qualifications and experience should include: 8+ years professional experience working with medium/large complex code bases Experience in Full Stack development Experience with one or more of the following programming languages: Java, Go, or Python Experience in REST API design and implementation Highly Proficient in HTML, CSS, the JavaScript ecosystem and familiarity with popular frameworks like React, Angular, Ember, Jest, Babel, and TypeScript Knowledgeable in UI/UX design principles Demonstrated proficiency with AI-native coding tools (Claude Code, Cursor, or GitHub Copilot) as a primary delivery vehicle, not a productivity add-on Working knowledge of prompt engineering, context management, and structured output patterns Familiarity with agent development concepts, tool use, function calling, approvals, and workflow chaining Awareness of secure AI coding practices including prompt injection, sandbox basics, and access control Strong communication and interpersonal skills Desire to collaborate and to develop strong and positive team relationships Attention to detail, organizational skills, a strong work ethic and the ability to work independently. Preferred Qualifications Bachelor’s degree in Computer Science or related field, or at least three years of proven experience in lieu of a degree Demonstrated ability to write clean, maintainable, and well-documented code. Database management, cloud technologies (AWS), and containerization (Docker, Kubernetes) Knowledge of React best practices Familiarity with DevOps tools and practices, including CI/CD pipelines Automated deployment tools (e.g. Terraform, Ansible, Jenkins) Experience with the AI-native development framework (e.g. BMad Method) Familiarity with MCP, A2A concepts, tool-connection patterns, and agent skill configuration Eval basics, writing test cases, applying LLM-as-judge concepts, and defining acceptance criteria for AI-generated output Experience tracing and debugging prompt chains, tool calls, and agent failures Unders
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