About SandboxAQ

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.

We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.

At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.

The Opportunity

SandboxAQ’s AI Simulation (AISim) division develops and applies Large Quantitative Models (LQMs) that are grounded in physics, chemistry, mathematics and biology to simulate molecular behavior with scientific precision and accelerate discovery in the physical world across biopharma, chemicals, advanced materials, healthcare, and so much more.

The AISim division is looking for a seasoned Product Manager to join this team to build and own the Data Platform that underpins AISim’s scientific discovery platform spanning Drug Discovery (BioSim) and Materials Design (ChemSim) applications. This includes the end-to-end data management lifecycle including how data is ingested from CROs and lab partners, automatically detected and reconciled, tracked end-to-end for lineage and provenance, and governed by sensitivity and field-of-use controls. Your charter spans the full journey of a dataset; from the moment it lands to the moment it is safely used in a model or exported as certifiable evidence.

This is a senior individual contributor role: you’ll lead through product craft and cross-functional influence, partnering closely with engineering, science, design, and trust/compliance. We’re customer-obsessed in practice and all platform decisions trace back to real internal and partner needs. We value collaborative problem solving, ownership, transparent communication, and humility.

Key Responsibilities

• Define and own the Data Platform roadmap across ingestion, auto-detection, schema reconciliation, and lineage

• Own the CRO and lab-partner ingestion-template product and the auto-matching UX, so partner data is usable the moment it lands

• Drive dataset-level provenance, sensitivity tagging, and field-of-use governance

• Design experiment-integration API schemas in partnership with the BioSim and ChemSim teams

• Own the federated data-management product that enables IP-safe data sharing across partners

• Define and track the metrics that matter including but not limited to time-to-usable per dataset, auto-match accuracy, and lineage completeness

Essential Skills & Experience

• 5+ years in product management, with depth in data platforms or data governance.

• Hands-on familiarity with ETL/ELT pipelines, data catalogs, and provenance / lineage tracking.

• Track record designing developer-facing data APIs and ingestion tooling.

• Experience defining data governance controls — access, sensitivity classification, and purpose / field-of-use restrictions.

• Ability to turn ambiguous, cross-team data problems into scalable, measurable products.

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

Highly Desired Skills & Experience

• Experience with scientific data formats (HDF5, SDF, CSV, JSON-LD).

• Understanding of federated learning and IP-sharing constraints in R&D contexts.

• Knowledge of regulated data governance (HIPAA, FedRAMP, GDPR, SOC 2, GxP / 21 CFR Part 11).

• Experience supporting audit, evidence-export, or compliance-attestation workflows.

• Familiarity with the drug-discovery or materials-research data lifecycle.

• MBA or equivalent business experience

Why Join Us?

We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work.

• Career Defining Work: Your work will directly accelerate the discovery of better drugs and better materials, advance human health, and enable safer and more sustainable technologies by helping customers put AI Simulation capabilities into real world use.

• Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.

• Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.

• Work-Life Balance: Fully remote, Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.

• Learning and Growth: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.

SandboxAQ Welcomes All

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.

Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.

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