Warren AI Specialist NJ

Job description

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 do AI 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 on value, 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 assigned solutions align with data, integration, cloud, infrastructure, security and service-management requirements. Lead evidence-based assessment of AI technologies, models, platforms and vendors 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, sharing reusable knowledge across internal teams and partners. Perform other duties as assigned. What you'd need 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; regulated-industry experience is strongly preferred. 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. Demonstrated ownership of production AI lifecycle practices, including testing, CI/CD, model and prompt versioning, observability, controlled deployment and remediation; MLOps or LLMOps experience is preferred. 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 required; ability to collaborate effectively across global teams and time zones. Commitment and alignment to Pharming's mission, core values and behaviors. Who we are We’re built on a simple belief: people living with rare diseases deserve more. Pharming is a global biotechnology company taking on some of the toughest rare disease challenges. We develop and commercialize innovative therapies for rare and ultra-rare immunological and genetic diseases with significant unmet need, where our scientific and commercial expertise, long-term commitment, and real partnership can help advance care. We put patients at the heart of our work. Their insights, along with those of caregivers, clinicians, scientists, and parters, shape our strategy, guide our decisions, and help turn science into meaningful progress. We keep it simple, act with urgency, and get it done – expanding access to approved therapies, advancing high-value pipeline programs, and building a leading global rare disease company. Our vision is simple: a world where people living with rare diseases don’t wait for progress or care. Together with the communities who inspir