
1001 - 5000 employees
Founded 1994
💼 Consulting
🏥 Healthcare
📦 Logistics
Consulting • Healthcare • Logistics
Pearson VUE is a global leader in computer-based testing, providing a wide range of credentialing and certification exams for various industries. They support test-takers and test owners by offering resources, scheduling options, and accommodations to ensure equitable access to testing. Their mission is to empower candidates and enrich communities through the delivery of high-stakes exams that validate professional skills and knowledge, contributing to career advancement and industry standards.
🕒 June 29
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1001 - 5000 employees
Founded 1994
💼 Consulting
🏥 Healthcare
📦 Logistics
Consulting • Healthcare • Logistics
Pearson VUE is a global leader in computer-based testing, providing a wide range of credentialing and certification exams for various industries. They support test-takers and test owners by offering resources, scheduling options, and accommodations to ensure equitable access to testing. Their mission is to empower candidates and enrich communities through the delivery of high-stakes exams that validate professional skills and knowledge, contributing to career advancement and industry standards.
• Own the design and evolution of scalable, secure, and high-performing web application architectures • Lead complex feature delivery across systems, ensuring alignment with long-term platform strategy • Act as a technical advisor to engineering and product leadership on design trade-offs and implementation approaches • Drive engineering best practices across code quality, testing, observability, and system reliability • Champion AI-powered development by actively leveraging tools (e.g., Cursor, Claude Code, LLM platforms) to enhance productivity • Define standards and best practices for AI-assisted coding, test generation, and design-to-code workflows • Lead adoption of generative AI and LLM integrations into enterprise applications and engineering processes • Partner with teams to operationalize AI-driven workflows and improve development efficiency at scale • Design, develop, and maintain full-stack web applications with a focus on performance, usability, and reliability • Contribute high-quality, production-grade code across frontend, backend, and APIs • Drive adoption of modern engineering practices including microservices, cloud-native development, and CI/CD • Mentor senior and mid-level engineers, fostering technical growth and engineering rigor • Conduct in-depth code reviews, providing actionable and constructive feedback • Influence engineering culture by promoting collaboration, ownership, and continuous improvement • Lead by example in driving accountability, technical excellence, and innovation
• 10+ years of experience in software engineering with a strong focus on web and distributed systems • Demonstrated success in leading complex technical initiatives and delivering at scale • Proven track record mentoring engineers and elevating team performance • Experience driving adoption of new technologies and engineering transformations (preferably AI-driven) • Experience operating in iterative, product-driven environments • Advanced expertise in software design, system architecture, and distributed systems • Strong experience in API design and management (REST/gRPC, versioning, scalability) • Deep understanding of cloud platforms (Azure or AWS) and cloud-native application design • Solid foundation in application security, data protection, and secure coding practices • Strong problem-solving and debugging skills across large-scale systems • Hands-on experience integrating LLMs, generative AI, and AI APIs (e.g., OpenAI, Anthropic, Azure OpenAI, AWS Bedrock) • Experience applying AI across SDLC: code generation, testing, documentation, and workflow automation • Understanding of ML concepts and AI adoption strategies across engineering teams • Proven ability to influence without authority and drive alignment across teams • Strong communication skills, with the ability to translate complex technical concepts to diverse stakeholders • High adaptability in fast-moving, ambiguous environments • Commitment to ethical engineering practices and responsible AI use.
• Remote
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