Leiden Principal AI Architect

Job description

Purpose of the role: The Senior AI Specialist is an individual-contributor role accountable for the enterprise technical direction, architecture and integrity of artificial intelligence capabilities that deliver measurable business value, better decision-making, automation and digital transformation across Pharming. The role converts enterprise strategy and high-value business priorities into scalable AI, machine-learning and generative-AI roadmaps, reference architectures and production capabilities that can be governed, reused and sustained across global functions. Reporting to the Head of AI, Data & Analytics, the Senior AI Specialist serves as a principal technical authority for applied AI within the AI & Transformation domain. The role leads the most complex, cross-portfolio and higher-risk AI challenges; shapes architecture, engineering and responsible-AI standards; advises senior business and technology leaders; assures the technical contribution of internal teams and strategic partners; and influences enterprise investment, platform and vendor choices without formal people-management responsibility. Role scope and (executive) accountability • Enterprise-wide technical accountability for the architecture, technical integrity, scalability and lifecycle coherence of complex AI, machine-learning and generative-AI capabilities and reusable implementation patterns across multiple functions, platforms and strategic use cases. • Delegated authority to define and evolve AI reference architectures, engineering standards, evaluation frameworks and lifecycle guardrails; approve solution designs and technical exceptions within delegated limits; and escalate material risk acceptance, policy, investment or enterprise-architecture decisions. • Lead resolution of the organization's most complex, ambiguous or high-impact AI challenges spanning data, systems, processes, functions and external partners, anticipating dependencies and systemic risks and establishing durable enterprise solutions. • Act as senior advisor to the Head of AI, Data & Analytics, architecture and governance forums and senior business leaders, shaping build-buy-partner decisions, platform and model choices, technical roadmaps and strategic vendor direction through evidence and expert judgment. • Accountable for advancing the maturity, reuse, reliability, responsible adoption and measurable technical outcomes of Pharming's enterprise AI capability and for developing technical talent through mentoring and standards leadership. Enterprise AI strategy, portfolio prioritization, formal governance ownership and budget accountability remain with the Head of AI, Data & Analytics and relevant governance forums. Areas of responsibility AI solution design and delivery • Architect and assure complex enterprise AI, machine-learning and generative-AI capabilities across multiple initiatives, ensuring coherent designs, production fitness, controlled integration and sustainable operation. • Translate strategic priorities and high-value business opportunities into multi-horizon technical roadmaps, reference architectures and sequenced delivery plans, balancing value, risk, data readiness, interoperability and long-term maintainability. • Establish reusable enterprise AI components, services, reference implementations and integration patterns that accelerate delivery, reduce duplication and enable consistent adoption across functions and partners. • Define and assure non-functional requirements and evaluation standards for reliability, performance, safety, observability, resilience, maintainability and operational support across the AI solution portfolio. • Set and evolve software-engineering, MLOps and LLMOps lifecycle standards, including version control, code review, CI/CD, model and prompt management, reproducible experimentation, release assurance and controlled change, and review conformance for critical solutions. • Sponsor resolution of cross-platform data, integration and infrastructure dependencies with data engineering, architecture and operations leaders so enterprise AI capabilities use trusted data and scale sustainably. Responsible AI, governance and lifecycle • Shape the technical implementation of responsible-AI policy by defining proportionate reference controls, human-oversight patterns, evaluation frameworks and guardrails for different intended uses and risk classes. • Lead technical risk assessment and design assurance for higher-risk or strategically significant AI use cases, advising business owners, governance stakeholders and control functions on residual risk, control effectiveness and release readiness. • Architect privacy, cybersecurity, access-control, data-protection, retention and compliance requirements into reusable AI patterns and critical solutions and drive resolution of material cross-functional control gaps. • Establish enterprise traceability and assurance expectations across models, prompts, data sources, configurations, evaluations, approvals and releases so AI capabilities can be governed, audited and changed in a controlled manner. • Oversee portfolio-level indicators for model and solution performance, reliability, drift, quality, safety and control health, identify systemic trends and lead remediation of material or recurring technical risks. • Serve as senior technical authority for regulated and GxP-relevant AI use cases where applicable, partnering with Quality, validation, privacy, security and regulatory stakeholders to establish compliant, risk-based technical approaches and evidence. Technical leadership and transformation • Set technical direction across the AI portfolio, chair or lead critical architecture and design reviews, resolve cross-workstream trade-offs and establish pragmatic standards and guardrails for internal teams and strategic partners. • Partner with senior business leaders, product and process owners and data and analytics leaders to frame AI opportunities, define value and risk hypotheses, shape investment cases and success measures, and ensure adoption and sustainable operating ownership. • Align AI architecture and roadmaps with Data Engineering, Enterprise Architecture, Enterprise Applications and Global IT Operations & Service Delivery, influencing enterprise data, integration, cloud, infrastructure and service-management priorities. • Lead strategic and evidence-based evaluation of models, platforms, tools and vendor capabilities, including technical due diligence and build-buy-partner recommendations based on value, scalability, interoperability, risk and total lifecycle economics. • Build organizational capability through senior-level mentoring, technical coaching, communities of practice, reusable guidance, executive AI literacy and selective external thought leadership, while remaining an individual contributor. • Perform other duties consistent with the senior accountability, strategic influence and professional scope of the role, as assigned. Your profile: Qualifications • Relevant bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering or a related field, or equivalent demonstrable professional experience. • Fluent English required; ability to collaborate effectively across global teams and time zones. Commitment and alignment to Pharming's mission, core values and behaviors. Experience: • Typically 10+ years of progressive experience in artificial intelligence, machine learning, data science, software engineering or related disciplines, including substantial experience at senior or senior technical level delivering and scaling complex production AI capabilities. • Proven enterprise track record architecting, building and operating AI or machine-learning capabilities across multiple functions, platforms or geographies and influencing technical roadmaps and investment decisions; regulated-industry experience is strongly preferred. • Deep and current expertise