• Design and architect unified testing frameworks that enable seamless portability of test cases across Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and simulation environments. • Build, configure, and maintain physical HIL benches and associated hardware interfaces (e.g., CAN adapters) to simulate real-world vehicle environments. • Integrate automated HIL testing directly into the Continuous Integration (CI) pipelines, ensuring code stability and preventing regressions prior to merging. • Collaborate closely with software engineering teams to understand their needs, identify and implement improvements in our Hardware-in-the-Loop (HIL) Infrastructure and Continuous Integration (CI) systems. • Monitor and report on runtime performance, system health, and reliability metrics across all HIL testing platforms.

• Design, build, and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance. • Develop reusable abstractions, templates, services, and workflows that standardize how teams build and manage data pipelines and data products. • Partner with Analytics, Applied-AI, Data-engineering and application teams to deliver platform capabilities that support business and clinical decision-making • Evaluate and integrate modern data and AI technologies with a focus on scalability, reliability, developer experience, and cost efficiency • Apply Generative AI technologies to improve data enablement, documentation, discovery, workflow automation, and platform usability • Promote software engineering best practices, including clean code, automated testing, CI/CD, infrastructure-as-code, monitoring, and secure data handling

• Build and maintain frontend platform, component library and web applications using modern front-end technologies such as TypeScript, React, and Next.js • Build reusable UI patterns, design tokens, components, and evangelize engineering guidance • Build and maintain a frontend platform that is machine-readable and API-first to serve AI agents alongside human users, with awareness of emerging commerce protocols (MCP, Universal Commerce Protocol) • Apply AI effectively throughout the software development lifecycle, including implementation planning, coding, review, testing, and quality improvement • Partner with product, design, and engineering peers to turn ambiguous requirements into well-scoped, high-quality deliveries • Own quality through testing, accessibility, observability, performance, and safe rollout practices

• Help design, build, and maintain backend systems and APIs • Improve reliability, observability, and automation of the Wikidata Query Service • Integrate Wikidata Platform services with other systems • Develop features and capabilities to ensure stability and scalability • Monitor production systems, respond to operational incidents • Support platform migrations and system upgrades • Contribute to deployment automation, CI/CD workflows • Participate in code reviews and design discussions