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Penetration Tester

On-sitefull timeMid-LevelWorldwide (On-site)
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WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Department: Data & Technology Solutions (DTS) Reports To: SVP Security and Compliance Location: [London/Hybrid 2 days a week in office] Position Type: Full-Time Role Overview The Product, Application and Offensive Security Engineer is responsible for embedding security directly into the design, development, testing, and operation of DTS products and platforms. This is a hands-on security engineering role. The role requires someone who can work directly with product and engineering teams, review designs, assess APIs, run threat models, test systems, coordinate penetration testing, identify vulnerabilities, and help teams remediate issues. The role ensures DTS products, APIs, data collaboration capabilities, AI-enabled workflows, and client-facing services are designed, built, and tested securely. It also owns the practical offensive security and adversarial assurance activity needed to test DTS products from an attacker’s perspective. The Product, Application and Offensive Security Lead will work closely with Product, Engineering, Architecture, Infrastructure, Security Operations, Privacy, Cloud and Platform Security, and the ISMS and Risk Officer to ensure security issues are identified early, fixed effectively, and tracked through governance where required. Key Responsibilities 1. Hands-on Product and Application Security Provide hands-on security support across DTS products and engineering teams. This includes: Reviewing product designs, technical designs, APIs, services, and integrations. Identifying security weaknesses in applications, workflows, and data flows. Advising engineering teams on secure implementation. Supporting secure design decisions during product discovery and delivery. Helping teams resolve security issues pragmatically without creating unnecessary delivery friction. 2. Secure Software Development Lifecycle (SDLC) Embed security into the software development lifecycle across DTS. This includes: Defining and applying secure engineering standards. Supporting secure coding practices. Reviewing CI/CD security controls. Supporting SAST, DAST, SCA, secrets scanning, dependency scanning, and container scanning. Helping teams triage, prioritise, and remediate security findings. Working with engineering teams to make security checks practical and repeatable. 3. Threat Modelling and Security Design Reviews Run threat modelling and security design reviews for new and changed capabilities. This includes: Facilitating threat modelling sessions with engineering and product teams. Reviewing authentication and authorization designs. Assessing API exposure, data flows, trust boundaries, and abuse cases. Identifying risks around tenant isolation, privilege escalation, data leakage, and misuse. Documenting key findings, recommendations, and residual risks. 4. Offensive Security and Adversarial Testing Carry out and coordinate offensive security testing across DTS products and platforms. This includes: Performing hands-on security testing of products, APIs, and workflows. Coordinating external penetration tests. Supporting red team and purple team exercises where required. Testing abuse cases and attacker paths. Testing access control, authentication, authorization, and data leakage risks. Validating remediation of security findings. Feeding material risks into the ISMS and Risk Officer for tracking. 5. API, Integration and Data Product Security Provide security assurance for APIs, integrations, and data products. This includes: Reviewing externally exposed APIs and partner integrations. Assessing rate limiting, authorization, tenant isolation, logging, abuse prevention, and data leakage controls. Supporting secure integration between InfoSum, Open Intelligence, Resolve, WPP Open, and third-party platforms. Reviewing data product workflows for misuse, excessive access, or unintended exposure. Working with Privacy Engineering on privacy-sensitive APIs, algorithms, and outputs. 6. AI and Agentic Security Testing Provide hands-on security review and adversarial testing for AI-enabled and agentic capabilities. This includes: Testing prompt injection, tool misuse, data leakage, and excessive agency. Reviewing how agents access APIs, data, tools, and workflows. Testing whether agent permissions can be bypassed or escalated. Assessing action boundaries and human approval points. Working with Identity, AI, and Data Access Governance to validate agent access models. Documenting AI and agentic security risks and remediation actions. 7. Vulnerability Triage and Remediation Support Help teams understand, prioritise, and fix security vulnerabilities. This includes: Reviewing vulnerability findings from scans, penetration tests, code reviews, cloud tools, and external reports. Prioritising findings based on exploitability, exposure, data sensitivity, and business impact. Working directly with engineers to define remediation options. Validating that fixes are effective. Supporting exception and risk acceptance decisions where remediation is delayed. Ensuring significant issues are visible through the DTS risk process. 8. Engineering Enablement and Security Coaching Act as a practical security partner to engineering teams. This includes: Providing secure implementation guidance. Creating lightweight security patterns and examples. Coaching engineers on common application, API, and AI security risks. Helping teams understand the “why” behind security requirements. Supporting a culture where security is part of product quality, not a separate approval gate. Key Accountabilities The Product, Application and Offensive Security Lead will be accountable for: Hands-on application and product security support across DTS. Secure SDLC guidance and practical adoption. Threat modelling and security design reviews. API, integration, and data product security reviews. Offensive security and adversarial testing activity. AI and agentic security testing. Vulnerability triage, remediation guidance, and fix validation. Coordination with ISMS/Risk to ensure material risks and exceptions are tracked. Helping engineering teams build secure systems without unnecessary delivery drag. Skills and Experience The successful candidate will have: Strong hands-on experience in application security, product security, offensive security, security engineering, or penetration testing. Good understanding of modern software engineering, APIs, SaaS platforms, distributed systems, and cloud-native applications. Experience with threat modelling and secure design reviews. Practical knowledge of common application and API security risks, including authentication, authorization, tenant isolation, injection, data leakage, privilege escalation, and supply chain risk. Experience using security testing tools and techniques across web applications, APIs, cloud services, and CI/CD pipelines. Familiarity with SAST, DAST, SCA, secrets scanning, dependency scanning, and vulnerability management workflows. Experience working directly with engineers to remediate findings. Understanding of AI and agentic security risks would be highly valuable. Ability to communicate clearly with engineering, product, architecture, security, and leadership stakeholders. A pragmatic, delivery-aware approach to security. Leadership Expectations The Product, Application and Offensive Security Engineer is expected to: Be hands-on and technically credible with engineering teams. Act as a trusted security partner, not just a reviewer or approver. Challenge insecure designs constructively. Help teams find practical ways to reduce risk. Prioritise issues based on real-world exploitability and business impact. Work across multiple DTS product areas without becoming a delivery bottleneck. Escalate material risks clearly through the appropriate governance routes. Promote secure engineering habits through practical guidance and example. Success Measures Success in the role will be measured by: Security being embedded earlier in product and engineering delivery. Reduction in high-risk application, API, and product vulnerabilities. Regular threat modelling and security reviews for critical DTS capabilities. Effective offensive and adversarial testing of products, APIs, and workflows. Faster remediation of penetration test and security testing findings. Improved security assurance for AI and agentic workflows. Engineering teams receiving practical, actionable security guidance. Material security risks being surfaced and tracked through the DTS risk process. Security being viewed by engineering teams as an enabler of trusted delivery rather than a blocker. You're open : We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working. You're optimistic : We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected. You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day. What we'll give you: Passionate, inspired people – We aim to create a culture in which people can do extraordinary work. Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry. Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge? #LI-Hybrid We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. Please read our Privacy Notice ( https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment ) for more information on how we process the information you provide.

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CybersecurityVia Greenhouse
Verified21 days ago

Senior Machine Learning Engineer

On-sitefull timeSeniorCopenhagen, Denmark
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WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Location Requirement This is a hybrid role based in Copenhagen, Denmark. Candidates must currently reside in Denmark or be willing to relocate independently, as relocation support is not provided for this position. About Open Intelligence We are the Activation arm of WPP Open Intelligence. Open Intelligence is a highly strategic initiative at the intersection of data science, advertising technology, and audience insights. Our team is building the data and ML systems that power the next generation of marketing and media intelligence, deeply integrated and adopted by the largest supply-side partners in the AdTech industry. With operations spanning the US, UK, and ongoing expansion into EMEA and APAC, our system continuously interacts with up to 98% of the population in our active markets. Based in our Copenhagen office, you will join a broader Open Intelligence team of roughly 50 people, including 14+ data scientists and a strong group of engineers working across data and ML production systems. Who We Are Looking For We are looking for a Senior ML Infrastructure Engineer with a strong background in infrastructure, platform engineering, data systems, or large-scale software engineering. You do not need to come from a pure ML infrastructure background to succeed in this role. What matters most is that you have strong engineering fundamentals and experience building robust, scalable, production-grade systems. You may have built cloud platforms, backend services, distributed data pipelines, or internal developer tooling, and you are excited to apply that experience to systems that support modern AI and ML workloads. You are comfortable working close to both engineers and data scientists, translating experimental or research-oriented work into reliable, maintainable production components. You care about system design, operational excellence, automation, observability, and maintainability. You value clean interfaces, strong testing practices, and infrastructure that can scale with growing demands. Beyond your technical skills, you are a strong communicator who can collaborate across disciplines, explain trade-offs clearly, and contribute to a high-trust, high-output team environment. Why we're hiring: We are hiring because we need experienced engineers who can help us design for scale, improve platform reliability, reduce operational friction, and build the foundations that allow advanced AI work to deliver real-world impact. To support this product evolution, our infrastructure is undergoing massive global expansion. By the end of this year, we will be fully operational across the rest of the EMEA and APAC regions. Concurrently, we are deepening our integrations to support even more of the largest supply-side partners in the AdTech industry. What you'll be doing: Design, build, and maintain scalable, production-grade infrastructure that supports data and ML workloads in the cloud, primarily on GCP. Collaborate closely with data scientists and engineering peers to translate research prototypes into robust, production-ready systems. Design and implement data and ML platforms with strong reliability, scalability, observability, and operational maturity. Identify and address technical debt, bottlenecks, and inefficiencies across infrastructure and platform components. Contribute to engineering best practices across CI/CD, version control, testing, automation, and repo maintenance. Participate in knowledge sharing, technical discussions, and continuous improvement across the team. What You Will Need 4+ years of experience in infrastructure engineering, platform engineering, data engineering, or large-scale software engineering. Strong practical experience with Python and SQL . Experience designing and operating systems in cloud environments such as GCP, AWS, or Azure . Familiarity with ML frameworks such as PyTorch or TensorFlow . Familiarity with MLOps tools such as MLflow , Kubeflow , or similar ML platforms. Experience with CI/CD, version control, API design, and testing best practices. Experience with building or supporting large-scale data or ML platforms, cloud platforms or other scalable production systems. A strong interest in building reliable, automated, and well-engineered platforms that support advanced AI and data workloads. A collaborative mindset and a willingness to work across disciplines in a fast-moving engineering environment. Nice to Have Familiarity with data processing and orchestration tools such as Spark, Flink, Airflow. Experience with infrastructure and deployment tooling such as Docker , ideally Kubernetes . Experience with strongly typed languages such as Java, Go, or C++ . Interest in using AI coding assistants to improve engineering productivity. Who you are: You're open : We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working. You're optimistic : We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected. You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day. What we'll give you: Passionate, inspired people – We aim to create a culture in which people can do extraordinary work. Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry. Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge? #LI-Hybrid We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. Please read our Privacy Notice ( https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment ) for more information on how we process the information you provide.

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AI / ML & Data ScienceVia Greenhouse
Verified22 days ago

Senior Data Engineer

On-sitefull timeSeniorCopenhagen, Denmark
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WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. About Open Intelligence: Open Intelligence (OI) is one of WPP’s most strategic bets — a data and AI initiative at the intersection of machine learning, advertising technology, and audience insight, built to power the next generation of media intelligence. OI operates at real scale, running across the US and UK and expanding rapidly across EMEA and APAC. Our Copenhagen team has ~50 people, including 14+ data scientists and a strong engineering group. We’re flat, high-trust and fast-moving: strong opinions loosely held, teamwork over ego, aim high and have fun. Why we're hiring: Open Intelligence is accelerating the development of its core AI capabilities, and we are strengthening our applied-AI and engineering group in Copenhagen. We need a Senior Engineer who can bridge the gap between AI experimentation and production software engineering — taking cutting-edge model research, multimodal embeddings, and agentic tools, and turning them into scalable, robust, and well-architected components that power products across WPP globally. We are looking for a Senior Engineer who cares about architecture and code quality as much as the AI. You write code others can build on, reason confidently about system design, and enjoy taking something experimental and making it robust. You hold a high bar but stay pragmatic — you ship incrementally and get value out early. We lean toward an engineering-minded profile, but a strongly technical data scientist or ML engineer with the same instincts is very welcome. What you'll be doing: Build and evolve the embedding spaces from off-the-shelf multimodal models. Build the MCP server and the agent/UI on top of it. Write high-quality, tested, well-architected code that others can build on. Work closely with data scientists and engineers across OI, turning experimental work into robust components. Contribute to technical direction and help raise the bar on design and quality. Who you'll be working with: You’ll join a small, sharp team working at the embedding and applied-AI layer of OI. We work fluidly across a few closely-collaborating teams, so exact ownership flexes — but this is what the team is building right now: Embedding spaces — using off-the-shelf multimodal models (text, image, video) to build well-designed, well-distributed embedding spaces that serve several downstream use cases. Not models trained from scratch — carefully engineered spaces that make the rest of OI’s AI work. An MCP server — the tool layer that exposes these capabilities to agents and applications. A chat agent + UI on top — turning those capabilities into something people can use and be impressed by. It’s a team-centric setup: the team grows and delivers together, and the remit evolves as OI does. The work spans clean architecture, high-quality code, and applied AI. What you'll need: 5+ years in software or ML engineering, with a strong track record of well-designed, well-tested systems. Strong Python, and cloud experience (ideally GCP — Vertex AI, Cloud Run, BigQuery). Comfort with modern AI building blocks: embeddings and vector search, LLM tooling and agents (MCP a plus). Solid architecture and system-design instincts; clean, testable code as a default. A strong communicator who works well across engineering and data science. Success attributes You untangle ambiguity rather than being intimidated by it. Pragmatic perfectionist: high standards, incremental delivery. Low ego, high trust; you make the people around you better. Thrive in a fast-paced, flat, entrepreneurial environment. Who you are: You're open : We are inclusive and collaborative; we encourage the free exchange of ideas; we respect and celebrate diverse views. We are open-minded: to new ideas, new partnerships, new ways of working. You're optimistic : We believe in the power of creativity, technology and talent to create brighter futures or our people, our clients and our communities. We approach all that we do with conviction: to try the new and to seek the unexpected. You're extraordinary: we are stronger together: through collaboration we achieve the amazing. We are creative leaders and pioneers of our industry; we provide extraordinary every day. What we'll give you: Passionate, inspired people – We aim to create a culture in which people can do extraordinary work. Scale and opportunity – We offer the opportunity to create, influence and complete projects at a scale that is unparalleled in the industry. Challenging and stimulating work – Unique work and the opportunity to join a group of creative problem solvers. Are you up for the challenge? #LI-Hybrid We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. Please read our Privacy Notice ( https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment ) for more information on how we process the information you provide.

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Data Engineering & BIVia Greenhouse
Verified27 days ago

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