AI Specialist

Pharming Group N.V.•Warren Township, NJ

3d•$115,000 - $155,000•Hybrid

About The Position

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 AI solutions that deliver measurable business value, improve decision-making, automate work, and support 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 the Warren, New Jersey office, with an expectation of two to three in-office days each week and flexibility to adjust schedules depending on business needs.

Requirements

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.
At least four years of progressive experience in artificial intelligence, machine learning, data science, software engineering, or related disciplines, including substantial hands-on ownership of complex production AI or machine-learning solutions.
Proven track record designing, deploying, and operating multiple AI or machine-learning solutions in complex or global environments.
Advanced practical experience with modern AI and machine-learning approaches, including generative AI, large language models, retrieval-augmented generation, model evaluation, agentic or automation patterns, and cloud-based AI services where relevant.
Advanced programming skills, particularly Python or an equivalent language used for AI and machine-learning development, together with strong software-engineering, API, integration, code-review, and maintainability practices.
Strong understanding of responsible AI, model risk, privacy, cybersecurity, data governance, explainability, and access-control principles, with demonstrated ability to translate governance and regulatory requirements into technical controls and evidence.
Ability to lead complex workstreams through expertise and influence, decide under ambiguity, communicate trade-offs to stakeholders, mentor colleagues, and resolve cross-functional challenges with limited supervision.
Fluent English and ability to collaborate effectively across global teams and time zones.
Commitment and alignment to Pharming's mission, core values, and behaviors.

Nice To Haves

Regulated-industry experience is strongly preferred.
MLOps or LLMOps experience is preferred.

Responsibilities

Own the technical design, development, testing, deployment, and transition to support of complex AI, machine-learning, and generative-AI solutions for prioritized business outcomes.
Translate prioritized use cases into solution designs and delivery plans; assess feasibility and data readiness; and select model, retrieval, agent, automation, and integration patterns based on value, risk, and maintainability.
Design and maintain reusable AI components, services, reference implementations, and engineering patterns to accelerate delivery, reduce duplication, and improve consistency.
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 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.
Resolve data, platform, and integration dependencies with data engineering and platform teams so solutions use trusted, governed data and progress from experimentation to sustainable production use.
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 assessments with business owners, governance stakeholders, and control functions; translate 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 ensure required control evidence is complete before release.
Maintain traceability across models, prompts, data sources, configurations, evaluations, approvals, and releases to support review, monitoring, auditing, and controlled changes.
Own lifecycle monitoring for assigned solutions, including performance, reliability, drift, quality, and relevant risk indicators; lead timely technical remediation when results or controls fall outside agreed tolerances.
Lead technical delivery and documentation of regulated and GxP-relevant AI use cases where applicable, working with Quality and validation stakeholders to meet quality, validation, and regulatory requirements.
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, turn 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 to align with data, integration, cloud, infrastructure, security, and service-management requirements.
Assess AI technologies, models, platforms, and vendors using evidence, and recommend fit-for-purpose choices based on value, scalability, risk, interoperability, and lifecycle impact.
Raise team capability through design reviews, mentoring, documentation, AI literacy, and communities of practice; share reusable knowledge across internal teams and partners.
Perform other duties as assigned.

Benefits

Flexible hybrid work schedule to promote a healthy work-life balance.
Competitive compensation package including annual target bonus.
Long-term incentive program.
401(k) plan with company match.
Paid Time Off (PTO).
13 company holidays per year.
Medical, dental, and vision benefit plans.
Flexible spending accounts.
Company-provided life insurance and short-term and long-term disability plans.
Optional accident, hospital indemnity, critical illness, and pet insurance plans.
Tuition reimbursement program.
Health and wellness program.
Choice of company-provided mobile phone or cell phone stipend.