Job description

If you are a current Jazz employee please apply via the Internal Career site Jazz Pharmaceuticals is a global biopharma company whose purpose is to innovate to transform the lives of patients and their families. We are dedicated to developing life-changing medicines for people with serious diseases — often with limited or no therapeutic options. We have a diverse portfolio of marketed medicines, including leading therapies for sleep disorders and epilepsy, and a growing portfolio of cancer treatments. Our patient-focused and science-driven approach powers pioneering research and development advancements across our robust pipeline of innovative therapeutics in oncology and neuroscience. Jazz is headquartered in Dublin, Ireland with research and development laboratories, manufacturing facilities and employees in multiple countries committed to serving patients worldwide. Please visit www.jazzpharmaceuticals.com for more information. Job Description Brief Description: The Associate Director, Enterprise AI Architect is a senior individual contributor responsible for maturing and leading the AI/ML architecture capability at Jazz. Reporting to the Director of Enterprise AI, this role will partner closely with senior leadership to develop and evolve the enterprise AI architecture strategy – including technology stack decisions, architectural standards, best practices, and AI-related policies and guardrails. The position focuses on strategic architecture and solution design rather than day-to-day model development, ensuring that Jazz’s AI systems are scalable, secure, compliant, and aligned with business needs. The ideal candidate is a pragmatic and intelligent technical leader who is organized, a clear communicator, and demonstrates strong critical thinking, diplomacy, and stakeholder management. They are passionate about the value AI can bring to the enterprise while remaining appropriately cautious about its power, risks, and responsible use. Essential Functions/Responsibilities Define and continuously enhance Jazz’s enterprise AI/ML architecture strategy, working with senior Data & AI leadership to align technology stack, operating models, governance frameworks, best practices, and policies with enterprise objectives. Establish AI architectural standards and reference architectures that ensure consistency, scalability, and security across all AI/ML initiatives. Establish and maintain AI governance processes and architectural guardrails, including guidelines for responsible AI use, model validation, risk management, and regulatory compliance, to ensure safe and ethical use of AI technologies in line with Jazz’s standards. Drive adoption of responsible AI practices (e.g. explainability, bias mitigation, data privacy protection) across the organization. Provide architectural oversight and technical guidance on AI/ML solution design and integration. Define overarching Enterprise AI architecture standards. Conduct architectural reviews and advise project teams on end-to-end AI/ML solution design – from data ingestion and model development to deployment, monitoring, and MLOps – ensuring solutions are robust, scalable, and aligned with enterprise data, security, and compliance standards. Serve as a subject-matter expert (SME) and trusted advisor on AI/ML architecture across technology teams. Evaluate and design AI/ML and Generative AI solutions, ensuring proposed approaches meet enterprise architectural standards and align with strategic goals. Challenge technical designs and assumptions to uphold Jazz’s requirements for reliable, compliant, and maintainable AI solutions. Contribute to discussions on AI use case priority using expertise in AI architecture to advise on feasibility, scalability, reliability, and how to avoid technical debt. Vet AI vendors and platforms in collaboration with our AI Development Lead, as well as Infrastructure and Digital Security teams. Together, conduct technical due diligence on solution feasibility, data handling, security, transparency, and overall operational maturity. During such evaluations, this role will focus on the proposed architecture viability and quality. Build credibility quickly with senior technical and business stakeholders through effective communication and deep expertise. Communicate complex architecture decisions and technical concepts in clear, business-relevant terms, and influence decision-making in cross-functional governance forums to align AI efforts with business objectives. Required Knowledge, Skills, and Abilities Strong communication skills with clear ability to communicate complex AI concepts to business leaders at all levels. Familiarity with AI governance and risk frameworks. Deep knowledge of AI/ML system architecture, including data pipelines, model development and deployment patterns, cloud-based ML infrastructure, and integration of AI solutions into enterprise systems. Proficiency with MLOps concepts, tools, and best practices, such as CI/CD, model versioning, experiment tracking, and monitoring (enabling reliable ML production deployments). Strong understanding of core machine learning algorithms and statistical modeling techniques, model evaluation, and real-world deployment considerations. Proficiency in one or more programming languages (e.g. Python, R) and ML frameworks (such as TensorFlow, PyTorch, scikit-learn). Strong understanding of modern Generative AI concepts and approaches: LLMs, RAG, fine-tuning, agentic patterns, evaluation, and guardrails. Significant hands-on experience with at least one major cloud platform (AWS, GCP, or Azure); AWS or GCP preferred. Familiarity with AI governance and risk frameworks (e.g., model risk management, responsible AI principles, emerging AI regulation). Required/Preferred Education and Licenses Bachelor’s degree or equivalent practical experience in a quantitative or technical field required. Advanced degree or equivalent preferred. 5–7 years of relevant experience in AI, machine learning, or data science required, 10 years preferred. Experience in pharmaceutical, life sciences, or another regulated industry strongly preferred. Experience evaluating and integrating third-party AI/ML solutions and vendor platforms strongly preferred. #LI-Remote Jazz Pharmaceuticals is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any characteristic protected by law. FOR US BASED CANDIDATES ONLY Jazz Pharmaceuticals, Inc. is committed to fair and equitable compensation practices and we strive to provide employees with total compensation packages that are market competitive. For this role, the full and complete base pay range is: $153,600.00 - $230,400.00 Individual compensation paid within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, and other pertinent factors. The goal is to ensure fair and competitive compensation aligned with the candidate s expertise and contributions, within the established pay framework and our Total Compensation philosophy. Internal equity considerations will also influence individual base pay decisions. This range will be reviewed on a regular basis. At Jazz, your base pay is only one part of your total compensation package. The successful candidate may also be eligible for a discretionary annual cash bonus or incentive compensation (depending on the role), in accordance with the terms of the Company s Global Cash Bonus Plan or Incentive Compensation Plan, as well as discretionary equity grants in accordance with Jazz’s Long Term Equity Incentive Plan. The successful candidate will also be eligible to participate in various benefits offerings, including, but not limited to, medical, dental and vision insurance, 401k retirement savings plan, and flexible paid vacation. For more information on our Benefits offerings please click here: careers.jazzpharma.com

Requirements

Must-haves

If you are a current Jazz employee please apply via the Internal Career site
Essential Functions/Responsibilities
Establish AI architectural standards and reference architectures that ensure consistency, scalability, and security across all AI/ML initiatives.
Drive adoption of responsible AI practices (e.g. explainability, bias mitigation, data privacy protection) across the organization.
Provide architectural oversight and technical guidance on AI/ML solution design and integration. Define overarching Enterprise AI architecture standards.
Serve as a subject-matter expert (SME) and trusted advisor on AI/ML architecture across technology teams.
Contribute to discussions on AI use case priority using expertise in AI architecture to advise on feasibility, scalability, reliability, and how to avoid technical debt.
Build credibility quickly with senior technical and business stakeholders through effective communication and deep expertise.
Communicate complex architecture decisions and technical concepts in clear, business-relevant terms, and influence decision-making in cross-functional governance forums to align AI efforts with business objectives.
Required Knowledge, Skills, and Abilities
Strong communication skills with clear ability to communicate complex AI concepts to business leaders at all levels.
Familiarity with AI governance and risk frameworks.
Deep knowledge of AI/ML system architecture, including data pipelines, model development and deployment patterns, cloud-based ML infrastructure, and integration of AI solutions into enterprise systems.
Proficiency with MLOps concepts, tools, and best practices, such as CI/CD, model versioning, experiment tracking, and monitoring (enabling reliable ML production deployments).
Strong understanding of core machine learning algorithms and statistical modeling techniques, model evaluation, and real-world deployment considerations.
Proficiency in one or more programming languages (e.g. Python, R) and ML frameworks (such as TensorFlow, PyTorch, scikit-learn).
Strong understanding of modern Generative AI concepts and approaches: LLMs, RAG, fine-tuning, agentic patterns, evaluation, and guardrails.
Familiarity with AI governance and risk frameworks (e.g., model risk management, responsible AI principles, emerging AI regulation).

Nice-to-haves

Significant hands-on experience with at least one major cloud platform (AWS, GCP, or Azure); AWS or GCP preferred.
Required/Preferred Education and Licenses
Bachelor’s degree or equivalent practical experience in a quantitative or technical field required. Advanced degree or equivalent preferred.
5–7 years of relevant experience in AI, machine learning, or data science required, 10 years preferred.
Experience in pharmaceutical, life sciences, or another regulated industry strongly preferred.
Experience evaluating and integrating third-party AI/ML solutions and vendor platforms strongly preferred.

Application prep

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Keywords to mirror

aimlci/cdmachine learningpythonawsgcpazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

401k