Role Description We are currently searching for a Full-Stack Engineer - Catalog to help modernize and scale a business-critical product catalog platform. This role involves end-to-end ownership across backend services, frontend applications, APIs, and relational databases. - Design, build, and deploy catalog features end-to-end - Develop APIs, business logic, data models, and React-based UI components - Participate in platform modernization initiatives - Use AI-assisted development tools for coding and test automation - Write and maintain automated tests - Collaborate with Product and Design teams Qualifications - Experience: 7–10+ Years - Backend expertise in C#/.NET, Go, Python, or Java - React or modern frontend framework experience - REST APIs and microservices architecture - MS SQL Server or PostgreSQL - CI/CD and automated testing - AI-assisted development tooling experience - Exposure to specific tools and has used AI in concrete workflows (e.g., 'I use Cursor for brownfield navigation and Claude Code for test generation') - Used AI for multiple SDLC steps: coding, testing, code review, documentation - Specific project with clear role for AI tooling and clear personal contribution - Exposure in validating or correcting AI output - Exposure on what worked and where AI fell short - Opinions on limitations of AI tools and how they compensate Requirements - Experience: 7–10+ Years - Backend expertise in C#/.NET, Go, Python, or Java - React or modern frontend framework experience - REST APIs and microservices architecture - MS SQL Server or PostgreSQL - CI/CD and automated testing - AI-assisted development tooling experience - Exposure to specific tools and has used AI in concrete workflows (e.g., 'I use Cursor for brownfield navigation and Claude Code for test generation') - Used AI for multiple SDLC steps: coding, testing, code review, documentation - Specific project with clear role for AI tooling and clear personal contribution - Exposure in validating or correcting AI output - Exposure on what worked and where AI fell short - Opinions on limitations of AI tools and how they compensate Benefits - Fully remote

• Be the technical reference for the cluster: architecture decisions, technology choices, and design reviews go through you • Close the end-to-end delivery loop: define, execute, deliver to production, and monitor • Mentor the cluster's Technical Owners and senior engineers: success is the team operating with less dependence on you • Participate in cross-cluster Tech Governance: architecture sessions and technical standards with other company leads • Represent the cluster's technical vision to product and management when needed • Lead by example in the use of AI in development as a process reference for the team

• Design and maintain scalable, secure software architectures aligned with business goals, resulting in robust and reliable systems • Introduce and implement best practices around OO, DDD, and microservices where appropriate • Use AI to streamline processes, reduce friction, and give time back to developers for the work that matters • Implement and enforce coding standards and best practices, driving measurable improvements in code quality and maintainability • Conduct regular code reviews with feedback that meaningfully reduces bug counts and improves software performance • Facilitate clear communication between development teams, product managers, and other stakeholders to keep projects aligned • Use data as your north star - leverage application data, third-party data, and our data warehouse to analyze and solve problems around both product impact and performance • Participate in our agile development process: sprint planning, story grooming, and standups • Champion our SDLC and secure coding practices across everything you ship

• Help build the next generation of AI-powered investigative products. • Join a small, senior team that combines application development and ML testing expertise. • Accelerate agent development, raise engineering standards, and turn work into a reusable AI platform. • Own ambiguous, high-impact technical problems end to end. • Influence architecture across teams and serve as a multiplier for engineers building AI-powered customer experiences.