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Johnson & Johnson

Makes prescription drugs and medical devices

Director, Computer-Directed Drug Design and AI-Native Molecular Design

Biology & BiotechConfirmed live in the last 24 hours
Full-timeSan Diego, CA, USA

About the Job

Requirements

  • A PhD in computational chemistry, theoretical chemistry, chemical physics, biophysics, cheminformatics, medicinal chemistry, or a related scientific discipline is required.
  • A minimum of 8 years of relevant small-molecule drug-discovery experience, including progressive scientific and people leadership, is required; equivalent combinations of training and experience may be considered.
  • Demonstrated impact across multiple discovery programs from hit identification through lead optimization, including contribution to a major progression milestone or candidate nomination, is required.
  • Deep applied expertise in computational chemistry, cheminformatics, molecular design, and multiparameter optimization, with judgment to select methods appropriate to the scientific decision, is required.
  • Strong medicinal chemistry and molecular architecture judgment is required, including the ability to interpret structure-activity relationships and balance potency, selectivity, pharmacokinetics, safety, synthesis feasibility, intellectual property, resources, and portfolio value.
  • Evidence that computational or AI-derived insights changed experimental priorities, compound designs, or program decisions and improved compound quality, learning speed, decision quality, or progression is required.
  • Experience applying and driving adoption of production-grade computational or AI-enabled capabilities in discovery workflows is required; direct responsibility for coding, model development, software engineering, or platform construction is not required.
  • The ability to co-lead in a matrix, influence governance, clarify decision rights, and build effective partnerships across portfolio-embedded scientific teams and specialist capability-development organizations is required.
  • Experience building, coaching, and scaling an application-focused computational drug-discovery team accountable for portfolio impact, collaborative delivery, and practical adoption is required.
  • Executive presence, scientific courage, sound judgment under uncertainty, and the ability to communicate complex evidence, tradeoffs, and recommendations clearly to senior leaders and multidisciplinary partners are required.
  • Working fluency in AI/ML-enabled discovery, generative molecular design, predictive modeling, protein structure prediction, agentic approaches, AI-assisted synthesis planning, and the scientific controls needed for responsible use is required.

Responsibilities

  • Co-own program strategy, molecular design priorities, and critical discovery decisions with medicinal chemistry, biology, project, therapeutic area, and developability leaders, with accountability for clear recommendations and measurable portfolio impact.
  • Translate target product profiles, biological hypotheses, project goals, decision points, risks, and constraints into integrated computational and experimental strategies that advance programs from target assessment through candidate nomination.
  • Lead the portfolio-embedded CD3 team as accountable computational molecular architects who combine computational models, experimental evidence, SAR, structural information, synthesis feasibility, safety, intellectual property, resource constraints, predictive properties, and portfolio value to ensure predictive models are used in design and guide compound decisions.
  • Orchestrate repeatable design–make–test–learn ways of working by defining scientific questions, decision criteria, feedback loops, escalation paths, knowledge-capture needs, and fit-for-purpose success measures with program teams, for incorporation into reusable platforms and production-grade capabilities in partnership with In Silico Discovery teammates.
  • Critically assess AI- and model-generated proposals, including assumptions, applicability, uncertainty, data quality, reproducibility, chemical tractability, and human-review requirements; establish appropriate scientific and responsible-use controls.
  • Integrate the portfolio-embedded CD3 team with partners in CI, D3S, and CADD Technical Development by creating shared priorities, clear interfaces, transparent handoffs, and operating rhythms that translate portfolio needs into reusable solutions across project teams.
  • Define scientifically grounded use cases, capability requirements, acceptance criteria, validation needs, and adoption measures for computational and AI-enabled solutions; provide structured portfolio feedback to teams accountable for development and lifecycle management.
  • Partner with CI, CD3, CADD Technical Development, and D3S to prioritize, validate, deploy, and continuously improve scalable platforms and workflows without duplicating development accountabilities.
  • Evaluate and select fit-for-purpose computational, AI/ML, generative, agentic, predictive, structural, simulation, cheminformatics, and automation capabilities based on scientific decision and operational context; guide responsible use by portfolio teams.
  • Drive adoption of validated AI-native capabilities through practical deployment, change leadership, training, transparent metrics, user feedback, and sustained behavior change.
  • Leverage emerging prompt-driven design-make-test-learn systems to translate program strategy and improve AI-generated proposals inspired by project context.
  • Influence program and portfolio governance by communicating evidence, uncertainty, risks, tradeoffs, resource implications, and recommendations clearly to senior leaders and diverse stakeholders.
  • Lead, coach, and develop a high-performing CD3 team; strengthen molecular architect judgment, project leadership, collaborative behaviors, responsible AI use, and AI-native scientific capability across ISD and the organization.
  • Integrate multidisciplinary contributors across chemistry, biology, structural biology, DMPK, toxicology, CI, D3S, CADD Technical Development, automation, Business Technology, and external partners while maintaining clear decision rights and accountability.
  • Evaluate external technologies and partnerships for scientific validity, strategic fit, scalability, and measurable discovery value; lead scientific collaborations and due diligence as appropriate.
  • Represent Johnson & Johnson and ISD through scientific collaborations, publications, presentations, consortia, and external engagement, integrating the Credo and Leadership Imperatives into decisions, talent development, and partnerships.
  • Perform other duties as assigned by the Senior Director, CD3, ISD.

Desired Qualifications

  • Experience across multiple small-molecule modalities, such as traditional Rule-of-Five and beyond-Rule-of-Five molecules, degraders, RIPTACs, molecular glues, and peptides.
  • Prior accountability as a small-molecule project leader, molecular design lead, or equivalent co-leader of program strategy and progression decisions.
  • Experience governing or applying agentic and human-in-the-loop discovery systems in a scientifically rigorous environment.
  • Experience translating portfolio use cases into requirements for cheminformatics, AI/ML, technical development, software, data, automation, or technology teams and achieving adoption across multiple programs.
  • Experience leading collaborations with academic groups, biotechnology companies, AI platform providers, automation partners, or contract research organizations.
  • A strong record of scientific and portfolio impact demonstrated through candidate delivery, patents, publications, presentations, capability adoption, or partnership outcomes.
  • Experience leading organizational change, establishing adoption and impact measures, and developing the next generation of AI-native drug-discovery leaders.
  • Ability to travel up to 30% domestically and internationally, as needed.

About the Company

Johnson & Johnson

Makes prescription drugs and medical devices

Johnson & Johnson develops prescription medicines and makes medical devices for hospitals, and unlike most big drugmakers, it runs both businesses under one roof. In 2015, its Darzalex became the first antibody drug approved for multiple myeloma, a blood cancer. Its medicines treat cancer, immune diseases such as psoriasis, and mental illnesses such as depression, and patented drugs bring in most of its sales. Its MedTech unit makes heart pumps, catheters that treat irregular heartbeats, surgical sutures, and Acuvue contact lenses. It was founded in 1886 to make sterile surgical dressings, is based in New Brunswick, New Jersey, and spun off its consumer brands, such as Tylenol and Band-Aid, as Kenvue in 2023.

Company size
10,001+
Company stage
IPO
Headquarters
New Brunswick, NJ
Founded
1886

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