AI Partnerships Lead

About the role

Benchling operates as the AI platform for biotech R&D, serving over 200,000 scientists globally and powering workflows for major organizations like Sanofi and Moderna. This position sits at the intersection of artificial intelligence and biology, tasking the lead with owning the company's most strategic AI relationships and defining its commercial footprint within the rapidly evolving AI ecosystem. The role demands a high-ownership operator capable of structuring complex, multi-dimensional deals that span data licensing, product integrations, and co-development arrangements. You will function as the primary architect of Benchling's engagement strategy with frontier model labs, scientific AI providers, and infrastructure partners, translating technical AI capabilities into commercial reality. Success requires fluency in both the language of AI research and the mechanics of enterprise deal-making, operating as a bridge between Benchling's internal product teams and senior external stakeholders.

Key facts

What you'll do

• Assume full lifecycle ownership for Benchling's highest-priority AI partnerships, managing relationships with frontier model laboratories, specialized scientific model providers, and critical infrastructure partners from initial sourcing through post-signature delivery and ongoing account management.
• Structure and negotiate sophisticated commercial agreements across the data economy, including inbound licensing of external datasets and models required to fuel Benchling's internal AI product roadmap and outbound licensing of Benchling's proprietary scientific data and platform capabilities to strategic partners.
• Execute a broad spectrum of deal types beyond data licensing, encompassing deep product integrations, co-marketing initiatives, and joint co-development projects, coordinating cross-functionally with Legal, Finance, Product, and Go-to-Market teams to operationalize commitments.
• Design and codify a repeatable, scalable playbook for AI ecosystem engagement, defining pipeline generation methodologies, pricing frameworks, standard deal structures, legal guardrails, and key performance indicators for partnership success.
• Proactively source, diligence, and evaluate the next generation of AI and ML companies - ranging from stealth-mode startups to public infrastructure giants - placing strategic bets on which entities become core Benchling partners.
• Serve as Benchling's senior representative at industry conferences, executive briefings, and high-stakes negotiations, engaging credibly with C-suite executives, technical founders, and research leadership at partner organizations.
• Translate complex, ambiguous technical concepts and uncertain market dynamics into clear, concise, and decisive written recommendations and deal summaries for internal leadership and legal review.
• Collaborate intimately with Benchling's technical AI and Product teams to understand model requirements, data schemas, and integration architectures, ensuring commercial terms accurately reflect technical feasibility and product strategy.
• Manage the end-to-end deal pipeline, running simultaneous workstreams across sourcing, qualification, discovery, valuation, term sheet negotiation, contract redlining, and implementation planning.
• Build and maintain a deep network within the AI/ML venture and research community, leveraging relationships to generate proprietary deal flow and market intelligence on emerging scientific AI trends.
• Drive internal alignment on partnership strategy by synthesizing feedback from Product, Engineering, Legal, and Sales leadership into coherent partnership roadmaps and resource allocation requests.
• Ensure all partnership activities comply with data governance, privacy, and security standards relevant to the life sciences industry, working closely with Legal and Security teams on risk mitigation.

Requirements

• Minimum four years of combined professional experience spanning partnerships, business development, enterprise sales, corporate development, management consulting, investment banking, venture capital, or relevant operational roles within life sciences, technology, or startup environments.
• Demonstrated bias for action and high comfort operating in ambiguity, with a proven track record of building processes and playbooks from scratch while simultaneously executing live, high-stakes commercial transactions.
• Established ability to manage and grow senior external relationships, engaging credibly and effectively at the executive level with CEOs, CFOs, CTOs, and heads of research or engineering at partner organizations.
• Strong functional knowledge of the AI/ML landscape, including model architectures, training paradigms, and the competitive vendor ecosystem, with the ability to translate technical concepts between research teams and commercial stakeholders; a formal technical degree is not required, but substantive technical fluency is essential.
• Full-cycle deal execution expertise, encompassing sourcing and qualification, deep discovery, complex negotiation, contract structuring alongside legal counsel, and post-close operational handoff and management.
• Exceptional written communication skills, capable of distilling complex, uncertain, and highly technical ideas into clear, concise, and decisive memos, term sheets, and strategic recommendations.
• Willingness and ability to work on-site in San Francisco five days a week, Monday through Friday, adhering to the company's in-person collaboration culture.
• Authorization to work in the United States; the job description does not explicitly mention visa sponsorship availability.

Nice to have

• Existing, demonstrable network and active engagement within the AI ecosystem, including relationships with venture capitalists, researchers at frontier labs, founders of AI-native startups, and executives at infrastructure providers.
• Prior professional experience in the life sciences sector, such as biopharma R&D, diagnostics, CRO/CDMO operations, or academic research administration.
• Advanced degree (PhD, Master's) in a scientific discipline such as biology, chemistry, bioengineering, computational biology, or a related field, providing deep domain context for scientific AI applications.
• Direct experience negotiating data licensing agreements, IP sharing frameworks, or API partnership terms specific to machine learning datasets or model weights.
• Background in product management or technical program management for AI/ML platforms, providing empathy for internal engineering counterparts.
• Experience working in a high-growth SaaS or platform company navigating the transition to AI-native product offerings.

Skills & tools

• Partnership Strategy & Business Development
• Complex Commercial Negotiation (Data Licensing, SaaS Agreements, Co-Development)
• AI/ML Landscape Fluency (LLMs, Foundation Models, Scientific ML, MLOps)
• Cross-Functional Leadership (Product, Legal, Finance, GTM, Engineering)
• Deal Structuring & Financial Modeling
• Executive Stakeholder Management & Communication
• Market Intelligence & Competitive Analysis
• Pipeline Management (Salesforce or similar CRM)
• Technical Translation (Research <-> Commercial)
• Contract Law Fundamentals (IP, Data Rights, Liability)

Practical notes

• This is a strictly on-site role based in San Francisco, CA, requiring presence in the office Monday through Friday; remote or hybrid arrangements are not indicated.
• The compensation package comprises a base salary range of $173,400 to $234,600 annually, supplemented by equity grants.
• The interview process includes a mandatory AI-focused exercise or discussion designed to assess the candidate's practical AI fluency, thinking process, and ability to integrate AI tools into daily workflows.
• Benchling is an equal opportuni