PALO IT is a global technology consultancy that crafts tech as a force for good. We design, develop and scale digital and sustainable products and services to unlock value across the triple bottom line: people, planet, profit. We do the right thing, and we do it right. We’re proud to be a World Economic Forum New Champion, and a B Corp-certified company.
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We are small enough to care locally, big enough to deliver globally (5 continents, 18 offices, +650 experts from +50 nationalities)
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We are robust and resilient (100% independent and 0 debt)
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We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence
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We are positive, courageous, caring, doers and committed to excellence
About Gen-e2
While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Our approach is a game-changer in productivity and quality, with a strong collaboration between AI generative and our best talents:
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We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design — with GitHub Copilot
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The quality consistently exceeds the output of our best traditional engineering teams
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A product repository houses all product artefacts, giving AI full project context for higher-quality generation
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A library of rules and prompts defines coding standards, design principles, and security guidelines
With Gen-e2, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence.
Your Role
As a Lead Design Ops, you will define, scale, and govern the Design Operations practice across multidisciplinary teams, enabling consistency, efficiency, and high-quality design delivery in a modern AI-first environment.
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Define and implement the Design Ops model, including governance, standards, and ownership frameworks
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Establish and scale design systems operations across web, mobile, and desktop platforms
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Build and maintain design tokens, component libraries, and system architecture for cross-platform consistency
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Design and optimize end-to-end workflows, ensuring seamless collaboration between design, product, and engineering
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Create and maintain living documentation systems to support scalability and knowledge sharing
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Define and manage tooling architecture, integrating platforms such as Figma, Storybook, and AI-powered tools
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Leverage AI (Figma AI, Copilot, Cursor) to automate processes and enhance design productivity
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Implement Design CI/CD pipelines, enabling continuous integration between design and development
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Define and track OKRs and KPIs to measure adoption, efficiency, and design quality
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Ensure accessibility standards (WCAG) and design quality benchmarks are consistently met
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Act as a strategic partner to Product, Engineering, and Leadership teams
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Drive alignment and influence without direct authority across distributed teams
Who You Are
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Proven experience in Design Ops, Design Systems, or UX Operations roles
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Strong experience building and scaling design systems and tokens across platforms
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Hands-on experience with Figma, Storybook, and modern design tooling ecosystems
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Understanding of design-to-code workflows and CI/CD for design systems
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Experience integrating AI tools into design workflows(Figma AI, Copilot, Cursor)
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Knowledge of accessibility standards (WCAG) and inclusive design practices
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Strong understanding of cross-functional collaboration (Design, Product, Engineering)
Soft Skills
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Strong system thinking and strategic mindset
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Ability to influence without authority
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Expertise in documentation and knowledge scaling
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Comfortable making decisions in ambiguous environments
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Strong communication and stakeholder management
AI-Native Engineering (Core Expectation)
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Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:
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Code scaffolding and refactoring
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Code generation and optimisation
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Test-cases and documentation generation
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Build applications through AI-driven development practices, including:
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AI-assisted debugging and troubleshooting
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Intelligent code completion and pattern recognition
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Automated documentation generation
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Apply prompt engineering best practices for reliable, repeatable engineering outcomes.