Drimva

Manifold Bio

Product Manager, AI Platform & Partnerships

$165K–$275K

Boston or San Francisco +2 · Manager · Full-time · Posted May 3, 2026

Location
Boston or San Francisco
Boston, Massachusetts, United States
San Francisco, California, United States
Experience
2–5 years; experience may be in product management, technical program management, alliance management, or BD, with at least part in AI/ML or computational product environments.
Education
Bachelor’s degree in a technical field (CS, engineering, biology, or related); advanced degree a plus.

About the job

Own the internal AI platform roadmap and manage external AI partnerships, translating AI and biology capabilities into products and platform assets.

What you'll do

  • Define the AI platform vision, roadmap, and success metrics, and translate R&D ideas into requirements and operating plans.
  • Prioritize, develop, and close AI partnerships; coordinate cross-functional execution and manage external deliverables.
  • Produce executive-ready memos, reports, decks, and demos to align stakeholders.

What they ask for

  • 2–5 years of product management, technical program management, alliance management, or BD experience, with some in AI/ML or computational product environments.
  • Bachelor’s degree in a technical field (CS, engineering, biology, or related).
  • Working knowledge of modern AI/ML concepts and their applications to drug discovery; familiarity with biology, protein engineering, drug discovery, or another applied scientific domain.
  • Strong written communication, cross-functional execution, strategic relationship management, and agentic coding skills.

Nice to have

  • Experience building or shipping products at a frontier AI lab, AI infrastructure company, or AI-first startup.
  • Experience structuring partnership terms, scaling partnership functions, or public communication through writing or talks.

Pay

$165K-275K (base salary)

Tools

AI/ML, foundation models, training and evaluation, agentic systems, scaling laws

AI focus

Lead product strategy for AI capabilities including protein design, foundation models, reasoning models, agents, and infrastructure; apply AI/ML to scientific problems and drug discovery.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 6, 2026 (UTC)