Job Description

We are looking for a Project Manager to join the CEO Office and drive high-priority, cross-functional initiatives across the company.
Reporting to the Chief of Staff, you will operate at the center of decision-making.

This role is designed for someone who thrives in ambiguity, enjoys solving complex business problems, and can move seamlessly from strategy to execution. You will work closely with senior leadership and have direct exposure to critical topics shaping the company’s growth.

What you’ll do

• Lead end-to-end delivery of strategic projects, from problem definition to execution and rollout
• Structure ambiguous topics into clear plans, with defined milestones, owners, and success metrics
• Coordinate cross-functional stakeholders (Product, Engineering, Finance, Sales, Compliance) to ensure alignment and delivery
• Track performance, manage risks, and ensure consistent delivery of outcomes
• Build and validate business cases (market sizing, unit economics, competitive positioning)
• Identify operational inefficiencies and implement scalable solutions
• Prepare high-quality materials for executive discussions and decision-making
• Leverage AI tools to improve workflows, automate processes, and enhance decision-making
• Support company-wide planning and operating rhythm (e.g. OKRs, strategic initiatives, governance cadences)

What we’re looking for

• 5+ years of experience in top-tier consulting and/or project management roles
• Experience in payments or fintech
• Proven track record of delivering complex projects in fast-paced environments
• Strong problem-solving and stakeholder management skills
• Hands-on experience using AI to solve real business problems (or building personal AI-driven projects)
• Data-driven mindset with the ability to prioritize and make decisions under ambiguity
• Fluent in English (French is a plus) 

Process: 

• HR Call
• Interview with Chief of Staff
• Interview with CPO 
• Case Study

Role Overview:

Netskope is seeking a high-caliber Privacy Engineering Staff Engineer to bridge the gap between legal compliance, data protection technology, and core product engineering. This is a dual-impact role: you will be responsible for the technical "Privacy by Design" controls for the Netskope platform while serving as a strategic deputy to the Global Privacy & Data Protection Officer (DPO).

As the Strategic Deputy to the Global Privacy & Data Protection Officer (DPO), you move beyond task completion to achieve high-level organizational influence.

• Global Compliance Strategy: Support the execution of a multi-jurisdictional privacy program that anticipates the rapid evolution of global data protection laws.
• Board & Audit Influence: Translate complex technical privacy risks into compelling, quantifiable narratives for the Audit Committee and Board of Directors.
• Risk Governance: Oversee the operational maturity of our privacy program within LogicGate, ensuring a closed-loop system of accountability, audit readiness, and incident response.
• DPIA & Rights Leadership: Act as the technical authority for high-risk Data Protection Impact Assessments (DPIAs) and ensure our Data Subject Rights (DSAR) engine operates at optimal efficiency.

You will be the lead privacy architect ensuring that Netskope’s innovation is inherently respectful of data.

• Component Design Review: Lead the privacy-first technical review of every new component within the Netskope platform, engaging with engineering at the "whiteboard phase" to eliminate risks before they reach production.
• PET Implementation: Direct the integration of Privacy Enhancing Technologies (PETs) such as differential privacy, homomorphic encryption, and k-anonymity into the Netskope product suite.
• AI Governance Leadership: Hold a seat on the AI Governance Committee whilst supporting the AI Ambassador program to ensure that AI innovations are built on a foundation of responsible data use.
• Technical Data Defense: Enhance DLP, DSPM, and AI/ML-driven security within our AWS and corporate environments to set the "Gold Standard" for internal data protection.

Key Responsibilities

Product Privacy Engineering & PETs

• Architectural Oversight: Review all new component designs within the Netskope platform to ensure structural compliance with "Privacy by Design" principles.
• PET Integration: Lead the design and implementation of Privacy Enhancing Technologies (PETs) such as differential privacy, homomorphic encryption, or k-anonymity within Netskope product features.
• Early Engagement: Act as a dedicated privacy consultant to product engineering teams during the ideation phase to identify and mitigate privacy risks before code is written.

Deputy Data Protection Officer (DPO) Functions

• Regulatory Support: Support the DPO in managing multi-jurisdictional compliance as the number of global privacy laws continues to rise.
• DPIA Leadership: Conduct and oversee Data Protection Impact Assessments (DPIAs) for high-risk processing activities, ensuring they meet the standard of global regulations.
• Privacy Leadership: Engagement with Netskope customers and partners on privacy and data protection concerns. Provide executive leadership to CISO, Legal and Privacy teams for some of the largest and most prestigious organizations in the world.

Technical Data Protection & AI Governance

• Advanced Controls: Utilize DLP (Data Loss Prevention) and DSPM (Data Security Posture Management) to secure the corporate data lifecycle.
• AI/ML Security: Implement data protection strategies specifically for AI/ML workloads, managing risks associated with training data and model inference.
• AI Advocacy: Serve on the AI Governance Committee and support the AI Ambassador program, fostering a culture of responsible AI use across the organization.

Platform Management

• LogicGate Administration: Manage and optimize the privacy module within LogicGate to track risks, audits, and compliance tasks.
• Netskope Corp Tenant: Take administrative responsibility of the Netskope corporate tenant’s privacy controls, ensuring our own use of the platform is a "Gold Standard" for customers.

Technical Requirements

• AWS Cloud Expertise:
• Cloud-Native Data Protection
• Infrastructure Security
• DSPM Integration.
• Software Engineering Fundamentals.
• API
• Data Architecture Knowledge
• AI/ML

Leadership Competencies & Soft Skills

• Strategic Influence: Ability to translate complex technical privacy risks into business-level impacts for the Audit Committee and Executive Leadership.
• Collaborative Engineering: Proven track record of building "security-first and privacy-first" cultures within engineering teams without slowing down the development lifecycle.
• Ethical Leadership: Strong judgment and integrity, particularly when serving on the AI Governance Committee to balance innovation with ethical data use.
• Stakeholder Management: Excellent communication skills to manage relationships with third-party vendors, legal counsel, and regulators.

Candidate Profile & Qualifications

• Experience: 5+ years in senior technical roles, preferably with a background in security engineering, privacy engineering, or data governance.

#LI-CS1

About The Role 💻 

We are looking for a Staff AI Engineer who thrives at the intersection of rapid experimentation and agile product development. In this role, you will be the bridge between the latest AI developments and tangible product impact. You aren't just following a roadmap; you are helping define it by proving what is possible with the latest frontier models and architectures. You will be responsible for the "quality loop": moving from a promising proof-of-concept to a highly reliable, optimized, and validated product.

What You’ll Be Doing 🚀

As a Staff AI engineer, you will be responsible for:

• Product-Centric Development: Designing and executing experiments to improve GenAI capabilities. This isn't just about "accuracy" in a vacuum—it's about optimizing for user value, reliability, and cost-effectiveness.
• Evaluation Systems: Building the "Golden Path" for quality. You will design and implement robust, multi-dimensional evaluation suites (e.g., using "LLM-as-a-judge," semantic checks, and unit tests) to ensure our features are production-ready and hallucination-resistant.
• Advanced RAG & Reasoning Optimization: Moving beyond "naive RAG." You will implement and tune advanced retrieval strategies (e.g., hybrid search, reranking, agentic retrieval) and optimize complex reasoning loops (e.g., CoT, ReAct) to make our current and future agents smarter and more reliable.
• Production-Grade Model Tuning: Leading the strategy for when, and if, to move beyond simple prompting. You will oversee supervised fine-tuning (SFT) and Parameter-Efficient Fine-Tuning (LoRA) workflows to adapt models to our specific product domains.
• Performance & Cost Engineering: Balancing the "Quality-Cost-Latency" triangle. You will find ways to maintain high-quality outputs while optimizing token usage and reducing inference latency.

Location 🌍 

The role is based in our tech hub in Madrid, Spain, but we are remote-friendly and open to the CET timezone +/- 2 hours.
Way of Working: Remote/Hybrid

What You’ll Need 👀

• Applied MLE Background: You have a proven track record of shipping Machine Learning functionality in a product-focused environment. You prefer "what works in practice" over "what works in theory."
• Bleeding-Edge Awareness: You are a "first adopter" of new AI technologies. You are intimately familiar with the trade-offs between frontier models and know how to swap or hybridize them for maximum impact.
• Experimental & Analytical Mindset: You understand the importance of controlled experiments. You know how to design a benchmark, create a "Gold Dataset," and use data to prove that a new prompt or model is an actual improvement.
• Practical LLM Expertise: Deep, hands-on experience with LLM orchestration, vector databases, and evaluation frameworks.
• Technical Stack Mastery: Expert-level Python and experience writing production-grade code.
• Product Mindset: You think about the user. You can identify when a model’s behavior might be technically correct but results in a poor user experience, and you know how to iterate to improve it.
• Experience: 5+ years of experience in ML or Software Engineering roles, with at least 2+ years of hands-on experience building and scaling GenAI/LLM-powered features.
• Self-starter, able to take ownership and initiative, with high energy and stamina
• Decisive and action-oriented, able to make rapid decisions even when they are short of information
• Highly motivated, independent and deeply passionate about sustainability and impact
• Excellent oral and written English communication skills (minimum C1 level-proficient user)

Nice To Have ✨

• Experience in a start-up
• Cloud AI Ecosystem: Familiarity with managed GenAI platforms and services such as OpenAI, Anthropic, AWS Bedrock, or GCP Vertex AI.
• Active Builder Credentials: A portfolio or GitHub showcasing side projects that experiment with the latest AI paradigms (e.g., multi-agent systems, local LLM execution, etc.).

What We Offer 🥁

• Competitive compensation, both in terms of base salary as well as equity plans that enable to you to share in our success
• Flexibility in ways of working both in terms of your schedule as well as your location, whether you prefer to work from home, the office, or abroad with access to a global network of co-working spaces 
• Generous paid time off schemes, including vacation, sabbatical, religious observance and compensation days
• Meaningful benefits including private healthcare coverage, fitness and wellness programs covered through Wellhub, working-from-home allowances to help you set up your home office and cover monthly expenses
• Professional development with annual training budget for conferences, courses, certifications and access to top market e-learning platforms
• Collaborative environment with multiple offices around the globe, regular team activities and events as well as employee-led resource groups