Jobs at PUMA Group

Build and operate production-grade LLM applications, agentic workflows, RAG and retrieval pipelines, AI memory architectures, and evaluation harnesses. Deploy and monitor AI services using cloud infrastructure, containers, APIs, and MLOps platforms. Configure AI gateways, manage model routing and costs, secure integrations, and optimize serving architectures. Collaborate with product, engineering, SRE, security, and software teams to deliver scalable AI capabilities.

Designs, builds, and operates scalable backend payment services for omnichannel commerce. Responsibilities include payment authorization, capture, refunds, tokenization, fraud prevention, gateway and enterprise-system integrations, observability, performance optimization, resilience, PCI-compliant architecture, and operational readiness. The role contributes to technical architecture, mentors engineers, reviews code, supports roadmap delivery, and uses AI-assisted development tools to improve quality and productivity.

Build and operate scalable Java-based microservices powering omnichannel basket, cart, pricing, promotions, checkout, order submission, and fulfillment experiences. Responsibilities include technical design, development, testing, performance optimization, caching, observability, reliability, monitoring, distributed tracing, and operational readiness. The role also involves supporting guest checkout, saved carts, multi-shipment orders, click-and-collect, real-time inventory, and AI-assisted engineering practices.

Designs, builds, and operates scalable backend services for basket, cart, pricing, promotions, and checkout across omnichannel commerce platforms. Integrates SFCC with order, inventory, ERP, customer, product, and fulfillment systems. Leads technical design, architecture decisions, observability, performance, reliability, code reviews, engineering standards, and mentoring. Develops resilient, low-latency services supporting complex checkout journeys and uses AI-assisted tools to improve delivery and code quality.

Build and maintain automated quality engineering solutions for payment, checkout, and transaction-processing platforms. Create functional, API, integration, contract, regression, performance, and end-to-end tests covering payment workflows, fraud controls, tax, promotions, reconciliation, and omnichannel experiences. Collaborate with product and engineering teams on quality strategy, test automation, compliance, observability, and production validation. Validate transaction integrity, security, scalability, device compatibility, and cross-browser performance.

Designs, builds, and maintains modern full-stack web applications, frontend features, backend services, APIs, and microservices. Leads technical delivery, architecture, performance, accessibility, security, observability, and cloud-native engineering initiatives. Collaborates with product, design, data, platform, and architecture teams; mentors engineers; supports production systems; and applies AI-assisted development and conversational commerce technologies.

Own marketplace product data quality and discoverability across product information, taxonomy, content, images, compliance, and marketplace feeds. Maintain marketplace requirements, map PIM data, run quality checks, resolve feed errors and suppressions, and track products through launch and sales. Diagnose poor visibility or conversion and coordinate root-cause fixes with business and content teams. Support SEO, marketplace search ranking, structured data, and AI-driven commerce initiatives.

Designs, deploys, and operates scalable, secure, reliable, and cost-effective cloud landing zones on GCP and Azure. Responsibilities include cloud architecture, infrastructure automation with Terraform or Ansible, security and governance, monitoring, cost optimization, troubleshooting, CI/CD support, documentation, and collaboration with infrastructure and engineering teams. The role requires hands-on cloud-native expertise across Kubernetes, Docker, microservices, and cloud operations.

Build scalable backend services, APIs, microservices, and event-driven solutions supporting personalization, recommendations, search, and AI-driven consumer experiences. Integrate AI/ML capabilities, develop React components, implement search using Elasticsearch or OpenSearch, and work with Kafka, databases, Redis, and cloud-native architectures. Ensure systems are secure, observable, resilient, and low latency while collaborating with AI/ML, data, and engineering teams.

Design, build, and maintain full-stack web applications supporting AI-driven product discovery, search, recommendations, personalization, and consumer experiences. Lead frontend technical design, develop React and TypeScript components, integrate backend APIs and AI capabilities, optimize performance and reliability, and contribute to backend services. Mentor engineers, participate in technical reviews, and collaborate with product, design, data, AI, and engineering teams.

Build and enhance full-stack, consumer-facing web applications for AI-driven product discovery, search, recommendations, and personalization. Develop reusable React components, integrate APIs and microservices, support backend services, and work with AI/ML and data teams. Contribute to scalable, secure, observable, and reliable solutions using search platforms, cloud services, databases, caching, and event-driven architectures. Collaborate cross-functionally with engineering, product, and design teams to deliver engaging digital experiences.

Build and operate scalable backend APIs, microservices, and integration services powering personalization, recommendations, search, and AI-driven consumer experiences. Own features from design through deployment, monitoring, and support. Collaborate with AI/ML and data engineering teams, improve service performance and reliability, contribute to system design and engineering standards, and mentor junior engineers.

Build and enhance consumer-facing full-stack web applications for AI-driven product discovery, search, recommendations, and personalization. Develop React and TypeScript interfaces, integrate APIs and microservices, contribute to Java and Spring Boot backend services, and improve performance, accessibility, scalability, reliability, and observability. Collaborate with AI/ML, data, backend, product, and design teams while participating in design and code reviews and using AI-assisted engineering tools.

Designs, builds, and operates scalable backend services, APIs, microservices, and event-driven systems supporting personalization, recommendations, search, and AI-driven consumer experiences. Partners with AI/ML, data, product, and engineering teams; integrates search and generative AI capabilities; improves performance, reliability, observability, security, and operational excellence. Leads technical delivery, mentors engineers, contributes to architecture reviews, and promotes engineering best practices.

Lead the architecture and development of scalable backend services for personalization, semantic search, recommendations, retrieval, conversational commerce, and agentic AI. Build low-latency APIs, microservices, vector search and retrieval pipelines, and enterprise integrations. Establish engineering standards, observability, reliability, responsible AI practices, and technical roadmaps while mentoring engineers and collaborating with AI/ML, data, product, and engineering teams.

Monitor systems and networks in a global 24/7 security operations environment, investigate and respond to cyber incidents, analyze post-event activity, assess vulnerabilities, and deploy countermeasures. The role requires familiarity with cloud security controls, threat intelligence, operating systems, network and web technologies, scripting, penetration testing tools, and vulnerability management. Strong analytical, communication, collaboration, and problem-solving skills are essential.

Provide L2/L3 IT support, manage Azure services, corporate network devices, Active Directory, and cloud infrastructure, ensuring reliable IT Security systems while collaborating in a global team.

Leads software engineering teams building search, browse, merchandising, recommendation, personalization, and consumer engagement capabilities. Owns roadmap execution, delivery planning, operational excellence, engineering quality, team metrics, talent development, and stakeholder collaboration. Drives experimentation, AI-assisted engineering, scalable services, and continuous improvement across digital consumer experiences.

Leads quality engineering strategy across PUMA’s direct-to-consumer technology landscape. Responsibilities include managing automation teams, designing scalable test frameworks, driving regression and API testing, integrating automated tests into CI/CD pipelines, defining quality metrics, and partnering with engineering, product, DevOps, SRE, and architecture teams. The role also advances shift-left practices, performance testing, observability, AI-assisted testing, and continuous improvement across web, mobile, commerce, integrations, and platform services.

Leads the Site Reliability Engineering organization for PUMA’s DTC platform. Defines SRE strategy, reliability standards, incident management, observability, resilience, cloud governance, infrastructure automation, and operational readiness. Oversees Google Cloud Platform operations, deployment safety, disaster recovery, FinOps, and peak-event preparedness. Builds and develops SRE teams, coaches engineering leaders, manages hiring and workforce planning, and promotes sustainable on-call practices across high-volume digital platforms.