Director of R&D, Artificial Intelligence

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

About Thermo Fisher Scientific

Thermo Fisher Scientific Inc. is the world leader in serving science, with annual revenue of approximately $50 billion. Our Mission is to enable our customers to make the world healthier, cleaner and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, increasing productivity in their laboratories, improving patient health through diagnostics or the development and manufacture of lifechanging therapies, we are here to support them. Our global team delivers an unrivaled combination of innovative technologies, purchasing convenience and pharmaceutical services through our industry-leading brands, including Thermo Scientific, Applied Biosystems, Invitrogen, Fisher Scientific, Unity Lab Services, Patheon and PPD.

How will you make an impact?

We are seeking a strategic, influential, technically fluent and hands-on Director, R&D AI Strategy and Transformation within the Chief Scientific Office (CSO) to shape how artificial intelligence is adopted across Thermo Fisher Scientific’s R&D organization.

The Director will help to develop the R&D AI roadmap, define the strategy for an AI-accessible knowledge layer, establish practical governance, and align leaders across a complex global matrix. The role will partner with scientific, product, business, data, technology, legal, cybersecurity, and other stakeholders to identify where AI can improve scientific work, knowledge access, portfolio decisions, and product development.

The role will also personally lead the design and prototyping of agentic AI solutions for the CSO office. The Director may develop prototypes directly or lead architecture, workflow design, orchestration, and evaluation in partnership with engineering teams.

What will you do?

AI strategy and transformation

Shape and advance the enterprise R&D AI roadmap, aligning priorities with scientific, product, portfolio, and business objectives.
Establish a consistent approach for identifying, evaluating, and prioritizing AI opportunities across R&D and adjacent functions.
Translate scientific and organizational needs into strategic initiatives, capability requirements, implementation pathways, and adoption objectives.
Define a federated operating model that clarifies roles, decision rights, reusable capabilities, and collaboration across businesses and functions.
Lead enterprise initiatives through influence, building alignment and commitment across a complex matrix.
Partner with R&D, Digital, IT, Data Science, Legal, and other teams as needed to drive AI adoption.

Knowledge layer and agentic AI

Define the roadmap for an R&D knowledge layer that enables trusted AI access to disparate internal and external information.
Establish principles for provenance, permissions, intellectual property, data quality, semantic consistency, traceability, and responsible access.
Partner with scientific, data, technology, and governance teams to determine how knowledge can be accessed and used responsibly by AI systems.
Personally lead the design, prototyping, and evaluation of agentic AI solutions for the CSO office.
Lead agent architecture, workflows, tool orchestration, and evaluation through direct development or in partnership with engineers.
Identify opportunities to extend successful CSO office prototypes across broader R&D, portfolio, and product-development workflows

Governance and organizational adoption

Establish an R&D AI governance framework covering prioritization, data and knowledge access, evaluation, human oversight, security, privacy, intellectual property, responsible AI, and lifecycle management.
Define the workflow, capability, and operating-model changes required to embed AI into R&D.
Establish measures of adoption, trust, reuse, maturity, and sustained use.
Ensure AI initiatives comply with regulatory, privacy, security, and ethical standards.

Technology, partnerships, and influence

Evaluate AI platforms, foundation models, scientific information services, data providers, technology vendors, and external collaborators.
Advise leaders on build-buy-partner decisions and lead selected pilots and technical evaluations.
Cultivate working contacts and relationships with software development and engineering teams across R&D to stay abreast of current digital investments
Translate emerging AI developments into clear strategic implications and recommendations for senior functional leaders.
Communicate complex scientific and technical concepts clearly to executive, scientific, product, and technology audiences.
Help define the future talent model and organizational capability required to scale AI across R&D.
Build relationships with technology vendors, academic institutions, and strategic partners.
Represent the organization at industry conferences and AI forums.
Conduct competitive assessments of AI capabilities within the life sciences industry.

What will success look like?

During the first 12–18 months, success will include

An aligned enterprise R&D AI roadmap and operating model.
An actionable knowledge-layer roadmap spanning internal and external information.
Valuable agentic AI prototypes for the CSO office.
An adopted governance framework and measurable progress in stakeholder engagement, trust, and sustained AI use.

How will you get here?

Education

Advanced degree (PhD preferred) in a scientific, engineering, computational, informatics, or related discipline relevant to life-sciences R&D.
The successful candidate will combine scientific depth with demonstrated leadership in AI strategy, transformation, and organizational adoption.

Experience

10+ years of relevant experience in AI strategy, technology transformation, scientific informatics, R&D strategy, or related roles.
Substantial experience shaping enterprise AI strategy, transformation, or capability-building initiatives in complex organizations.
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