Senior Product Software Engineer - Frontend

Senior Software EngineerDisney Growth, Commerce, and Identity Experience organization powers the foundational user experiences across Disney+, Hulu, ESPN+, and other Walt Disney Company business units. These experiences are built on a shared identity platform that enables secure, seamless authentication, registration, and account management for hundreds of millions of users globally.The Identity Client Experience team owns and evolves the client-side governance platform that powers trusted, compliant, and consistent user experiences across Disney's streaming ecosystem — including privacy and consent management, age verification, parental controls, Kids Mode, analytics governance, and policy-driven feature control. These systems are essential to ensuring every interaction across Disney+, Hulu, and ESPN+ is compliant by default, regionally adaptive, and consistent across web, mobile, and living room devices.We are seeking a Senior Software Engineer with strong cross-platform instincts and a passion for building secure, scalable, and policy-driven client experiences. In this role, you will design and develop core governance capabilities used across all of Disney's streaming platforms, collaborate closely with legal, privacy, product, and partner teams, and help shape the future of identity and data governance on the client.Responsibilities:Own the design, development, and successful deployment of medium-to-large size software solutions, ensuring performance, quality, scalability, and security.Drive software engineering best practices, including design, code quality, security and testability within the team.Exhibit deep and broad technical expertise, with hands-on proficiency in key functional/specialty areas.Serve as a primary technical resource for the team, offering guidance on technical issues and new feature development.Participate in the design and delivery of features that integrate with LLM-backed services. For example streaming chat surfaces, structured-output forms, retrieval-grounded search, and tool-use interactions, partnering with senior AI-application engineers on the team.Help establish and refine team practices for using AI coding tools (Cursor, Claude Code, or equivalent) effectively and responsibly in day-to-day development.Execution & Impact:Solve complex technical problems with an innovative and experimental can-do attitude grounded by advanced technical skill and technique.Conduct thorough code reviews, focusing on requirements, design and coding standards, readability, testability, and optimization.Mentor and guide the work of less experienced engineers to develop solutions.Identify opportunities and recommend the development or implementation of solutions to improve products or processes with each iteration.Document technical details for assigned features, fixes, and projects.Autonomy & Influence:Work independently with minimal guidance, applying judgment in selecting methods and techniques to resolve issues or satisfy requests.Make timely, informed technical decisions that moderately influence the work of team members and related projects.Participate in developing new technical approaches and tools.Communicate complex technical information effectively to both technical and non-technical audiences.Basic Qualifications:Minimum of 5 years of hands-on software engineering experienceBachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experienceStrong problem-solving skills and ability to write clean, maintainable, scalable codeProficiency in TypeScript/JavaScript; experience building client-side features in web or device environmentsExperience building and consuming RESTful APIs and working with state management patternsFamiliarity with authentication and authorization conceptsKnowledge of CI/CD pipelines and deployment tooling (GitHub Actions, GitLab CI, or equivalent)Experience with testing frameworks for unit, integration, and/or end-to-end coverageStrong cross-functional communication skillsPreferred Qualifications:Experience shipping client features on at least one native or device platform: iOS (Swift), Android (Kotlin), Roku (BrightScript), or Web (TypeScript/JS)Familiarity with cross-platform SDK integration patterns and shared client library developmentExperience with server-side rendering and modern React frameworks.Experience building or contributing to a shared component library or design system at scale.Experience with real-time UIs — streaming responses, WebSockets/SSE, optimistic updates, partial rendering.Performance engineering experience — Core Web Vitals, bundle optimization, profiling, rendering performance.AI-assisted development:Hands-on experience using agentic coding tools (Cursor, Claude Code, GitHub Copilot, or equivalent) as a regular part of your workflow — beyond inline autocomplete.Experience authoring durable project context for AI tools — AGENTS.md, CLAUDE.md, Cursor rules, custom skills, or comparable artifacts that encode team conventions.Familiarity with plan-first / spec-first workflows when working with coding agents (plan mode, milestones, review gates) and with structured review of AI-generated code (hallucinated APIs, plausible-but-wrong logic, security regressions, prompt-injection risk in agentic flows)AI application exposure (growth-area; not required):Experience integrating LLM APIs (OpenAI, Anthropic, Amazon Bedrock, Azure OpenAI, or equivalent) into web applications, even at the level of one or two shipped or seriously prototyped features.Experience building user-facing surfaces for LLM features — streaming UIs, tool-use / function-calling interactions, structured output rendering, citation and grounding UX, regeneration and interruption flows.Familiarity with the TypeScript AI ecosystem (Vercel AI SDK, Mastra, LangChain.js, official OpenAI/Anthropic TS SDKs, MCP clients) or working knowledge of the Python AI ecosystem (LangChain, LlamaIndex, evaluation frameworks).Awareness of LLM-application concerns in production: evaluation strategies (golden datasets, regression checks, LLM-as-judge with appropriate skepticism), observability and tracing (Langfuse, LangSmith, Helicone, OTel-based), token accounting, latency budgets, caching, and content safety.Awareness of AI-specific risks in user-facing surfaces — prompt injection via user input or retrieved content, output validation, PII handling, and responsible-use considerations.Domain & ways of working:Experience building internal tools, developer platforms, or operations applications at scale.Experience working in a large, cross-functional engineering organization — coordinating across teams, navigating shared platforms, and contributing to org-wide standards.Experience in media, entertainment, sports, or streaming technology is a plus but not required.