About this role
This Director-level Scientific Fellow leads Vertex’s agentic AI co-scientist initiative across scientific functions. The role sets the scientific strategy, architecture, evaluation framework and delivery plan for capabilities that support scientific reasoning, hypothesis generation, experimental planning and decision support. It covers both internal development and rigorous assessment of external tools.
Responsibilities
- Lead a matrixed scientific, computational and technical team; translate priority research needs across projects, sites and modalities into a sequenced roadmap with clear milestones, risks and outcomes.
- Guide development of scientific system skills, integration of existing datasets and methods, and the design of agent roles and orchestration patterns. Work with domain experts to identify valuable drug-discovery use cases and move capabilities from prototype to supported adoption while retaining human scientific judgment and accountability.
- Evaluate commercial, partnership, open-source and internal options using evidence-based benchmarks and governance to inform build, buy, partner or integrate decisions. Set validation and acceptance criteria covering correctness, relevance, novelty, reliability, reproducibility, provenance, uncertainty, usability and impact on scientific decisions.
- Define workflows connecting agents, models, tools, data, literature, compute and expert review. Partner with platform and infrastructure leaders on trusted data access, knowledge management, integration and scalable compute. Communicate strategy, tradeoffs, progress and resource needs to senior leaders, and drive adoption and change management.
Qualifications
- Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Computational Chemistry, Bioinformatics, Engineering or Applied Mathematics, with 10+ years of relevant scientific drug-discovery and research experience, or comparable training and experience.
- Senior scientific and technical leadership in drug discovery, life sciences, AI/ML, computational science or a related field; experience delivering cross-functional initiatives and developing, evaluating, deploying or governing advanced AI or data-driven systems in rigorous scientific settings.
- Deep knowledge of research workflows, LLMs, agentic systems, scientific foundation models, retrieval, tool use, planning and evaluation. Strong executive communication, stakeholder management and mentoring skills; commitment to responsible AI, reproducibility, data governance, cybersecurity, privacy and human oversight. Recognized scientific impact through publications, patents, deployed capabilities, presentations or comparable contributions is expected.
Location and compensation: Boston-based. The hybrid arrangement requires three days per week onsite; employees may instead choose five days onsite. The base salary range is $216,400–$324,600, with eligibility for an annual bonus and equity awards. Listed benefits include medical, dental and vision coverage, paid time off, educational assistance and a 401(k).