AI Specialist

Location: Warren

Summary The AI Specialist is an individual-contributor role accountable for the end-to-end design, development, deployment and lifecycle performance of secure, reliable and responsible artificial intelligence solutions that deliver measurable business value, better decision-making, automation and digital transformation across Pharming. The role translates prioritized business outcomes, enterprise AI direction and architectural standards into production-ready AI, machine-learning and generative-AI capabilities that can be adopted sustainably across global functions.

Reporting to the Head of AI, Data & Analytics, the AI Specialist works with high autonomy and serves as technical authority for assigned AI products and initiatives. The role leads complex cross-functional delivery, makes delegated technical decisions, assures engineering and responsible-AI quality, guides colleagues and partners, and coordinates with business, data, architecture and control stakeholders to deliver valuable, secure and supportable solutions.

This is a hybrid role based in our Warren, NJ office with an expectation of 2-3 in office days in office each week and the flexibility to adjust schedules depending on business needs. What you'd doAI solution design and delivery

Own the technical design, development, testing, deployment and transition to support of complex AI, machine-learning and generative-AI solutions that address prioritized business outcomes and operate reliably in production

Translate prioritized use cases into solution designs and delivery plans; challenge feasibility and data readiness and select model, retrieval, agent, automation and integration patterns based onvalue, risk and maintainability.

Design and maintain reusable AI components, services, reference implementations and engineering patterns that accelerate delivery, reduce duplication and improve consistency across Pharming.

Define solution-level quality and evaluation criteria and engineer for reliability through automated testing, monitoring, observability, error handling, performance management, documentation and operational support practices.

Lead application of modern software-engineering and AI lifecycle practices, including version control, code review, CI/CD, model and prompt versioning, deployment automation, reproducible experimentation and controlled release management.

Drive resolution of data, platform and integration dependencies with data engineering and platform teams so assigned AI solutions use trusted, governed data and progress from experimentation to sustainable production use Responsible AI, governance and lifecycle

Apply responsible-AI standards and define solution-specific controls, human oversight and technical guardrails proportionate to intended use and risk.

Lead solution-level AI risk assessment with business owners, governance stakeholders and control functions, translating risk classification, intended use, quality expectations and governance requirements into enforceable technical controls and evidence.

Embed privacy, cybersecurity, access control, data protection, retention and compliance requirements into solution architecture and deployment and assure that required control evidence is complete before release.

Establish and maintain traceability across models, prompts, data sources, configurations, evaluations, approvals and releases so solutions can be reviewed, monitored, audited and changed in a controlled manner.

Own lifecycle monitoring for assigned solutions, including performance, reliability, drift, quality and relevant risk indicators, and lead timely technical remediation when results or controls fall outside agreed tolerances.

Lead the technical delivery and documentation of regulated and GxP-relevant AI use cases where applicable, working with Quality and validation stakeholders to meet Pharming's quality, validation and regulatory requirements.

Technical leadership and transformation

Provide hands-on leadership for complex AI initiatives, set implementation direction, assure adherence to standards, and make risks, trade-offs and exceptions visible to decision-makers.

Partner with business, product, data and analytics owners to define value and success measures, convert high-value opportunities into usable solutions, and lead transition from proof-of-concept to sustainable production.

Coordinate technical dependencies with Data Engineering, Enterprise Architecture, Enterprise Applications and Global IT Operations & Service Delivery so…