Purpose of the Function
This role will define and lead the strategic direction for our enterprise Artificial Intelligence (AI) platform and Machine Learning Operations (MLOps) frameworks, including LLMOps, establishing the core foundation for AI-driven innovation at argenx. It is accountable for providing a robust, scalable, and efficient environment that enables the end-to-end lifecycle of AI models, from experimentation to production. This position will drive a multi-year platform roadmap that accelerates the delivery of high-impact AI solutions, ensuring our AI initiatives are operationalized effectively, responsibly, and at scale to drive tangible business outcomes. The role is also responsible to introduce enterprise wide AI tools from Open AI, Anthropic, Microsoft and other partners.
Roles & Responsibilities
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Provide overall leadership for the enterprise AI platform and MLOps frameworks (including LLMOps), managing all associated resources including personnel, vendors, and budget to ensure the robust operationalization of AI models.
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Lead the strategic direction and roadmap for the AI platform, ensuring it provides an efficient and scalable environment for the end-to-end model lifecycle. Drive the adoption of standardized MLOps practices and frameworks to accelerate model development, improve reliability, ensure reproducibility, and enable governance.
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Partner with data science teams and business units to ensure the AI platform meets their evolving needs, removes friction, and directly enables the creation of tangible business value.
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Own the full lifecycle management for the AI platform portfolio, including Agentic AI, making strategic investment decisions about new technologies, tools, upgrades, and retirements.
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Own the full lifecycle management for the Enterprise AI tools, making strategic investment decisions about new technologies, tools, upgrades, and retirements.
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Ensure the AI platform adheres to the highest standards of security, compliance, and ethical AI principles, in close partnership with governance and security teams.
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Champion a culture of engineering excellence and innovation within the platform team, fostering an environment that challenges the status quo in pursuit of breakthrough AI capabilities.
Skills and Competencies
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Knowledge of modern AI/ML platform architectures, MLOps frameworks, and the ecosystem of tools for model development, training, deployment, and monitoring.
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Knowledge and understanding of Agentic AI frameworks and managing lie cycle of AI Agents
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Skilled in shaping enterprise technology strategy and developing multi-year roadmaps specifically for AI and Machine Learning platform portfolios.
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Knowledge of financial management and procurement, with experience managing large budgets, complex vendor contracts, and technology lifecycle planning.
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Skilled in leading senior technical and MLOps engineering teams, and influencing data science leaders to drive alignment on technical direction and best practices.
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Ability to work collaboratively and effectively together within cross-functional teams and networks.
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Demonstrated communication skills, within a multi-cultural and multi-lingual global environment.
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Is agile and demonstrates adaptability, comfort with ambiguity, trust-building, and resilience.
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Derives energy from operating in a dynamic, complex, fast-moving, and frequently changing business environment.
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Demonstrable experience with project management, proactive planning, priority setting, and securing alignment.
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Drives toward outcomes.
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Ambitious, inquisitive naturally, a quick study, with demonstrated eagerness to continuously learn, self-improve and develop. This includes being comfortable giving and receiving feedback in a diverse environment.
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Passionate and prepared to lead and contribute to our culture, which is driven by our corporate values of co-creation, innovation, empowerment, excellence, and humility.
Education, Experience & Qualifications
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Bachelor's or Master Degree preferred in Computer Science, Engineering, Artificial Intelligence, Data Science or related fields relevant to the designated function.
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Experience in a senior leadership role accountable for enterprise-scale AI platforms, MLOps, or data science infrastructure in a global, regulated industry. "12+ Years".
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Experience shaping long-term AI technology strategy, managing significant budgets, and leading teams of senior engineers or MLOps specialists. "8+ Years".
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Experience deploying Gen AI technology, introducing LLMs and enterprise AI tools. "3+ Years".
Other
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25% travel required
