Head of Enterprise GTM

AfterQuery is an applied research lab curating data solutions for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models. In doing so, we can make expertise that once took a lifetime to build available to anyone who needs it.

Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI. Forbes reported that we could be YC's fastest unicorn, reportedly raising at a $3.2 billion valuation. We're based in San Francisco and backed by leading investors including Altos Ventures, BoxGroup, and Y Combinator and angels from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, and Microsoft AI.

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  Take full ownership of AfterQuery's enterprise go-to-market strategy, commercial execution, and overall customer acquisition efforts.

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  Define and execute the strategy for identifying, pursuing, and closing high-value enterprise opportunities across AI, technology, and other relevant industries.

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  Personally drive outbound prospecting, relationship development, pipeline generation, and strategic account acquisition while building the foundation for a scalable sales organization.

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  Establish our enterprise sales motion, including target account strategy, qualification, positioning, pricing, deal structures, and commercial negotiations.

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  Identify the highest-value customer use cases for custom evaluations, data generation, model training, and post-training engagements.

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  Build the processes, playbooks, metrics, and operating cadence needed to create a repeatable and scalable GTM function.

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  Establish, hire, and lead a high-performing enterprise GTM team as the business scales, setting clear expectations for performance, accountability, and execution.

• Build and own relationships with senior executives, business leaders, and technical decision-makers across large enterprise organizations.

• Lead consultative discovery to understand customer workflows, business objectives, technical requirements, and opportunities for AI-driven improvement.

• Translate customer problems into compelling commercial opportunities, developing proposals that connect AfterQuery's capabilities to measurable business outcomes.

• Own the full sales cycle, from initial outreach and discovery through solution scoping, pricing, contracting, and deal closure.

• Structure sophisticated enterprise agreements, balancing customer needs, commercial economics, delivery requirements, and long-term business value.

• Lead complex commercial negotiations, including pricing models, engagement structures, contract terms, and expansion opportunities.

• Develop strategic account relationships that generate repeat business, long-term partnerships, and broader enterprise adoption.

• Partner closely with AfterQuery's research and technical leadership to understand our capabilities and translate them into differentiated enterprise solutions.

• Identify and scope technical engagements involving model evaluations, failure analysis, training data, and post-training approaches such as supervised fine-tuning and reinforcement learning.

• Work with research and technical teams to determine feasibility, resource requirements, timelines, and delivery expectations before committing to customer engagements.

• Translate customer requirements into clearly defined scopes of work, deliverables, success metrics, and commercially viable engagement structures.

• Ensure alignment between what is sold commercially and what can be successfully executed by our research and delivery teams.

• Bring customer feedback, market intelligence, and emerging enterprise needs back to research leadership to inform future capabilities and opportunities.

• Maintain ownership of customer engagements beyond the initial contract, ensuring successful execution and delivery against commercial commitments.

• Lead the transition from signed agreement to active engagement, coordinating researchers, technical teams, and operational resources.

• Establish clear accountability for project scope, milestones, deliverables, success criteria, and customer communication.

• Proactively manage delivery risks, resolve escalations, and ensure customer expectations remain aligned with execution.

• Monitor engagement performance and commercial outcomes, identifying opportunities to improve delivery models, engagement economics, and customer satisfaction.

• Turn successful engagements into long-term strategic partnerships, repeat business, case studies, and opportunities for account expansion.

• 7–10+ years of experience in enterprise sales, strategic business development, commercial leadership, or enterprise GTM at a high-growth technology company.

• A proven track record of independently building enterprise pipelines, acquiring major customers, and closing complex, high-value commercial agreements.

• Experience leading enterprise GTM or sales functions, ideally in an early-stage or high-growth company where you built the commercial motion from the ground up.

• Strong commercial judgment and experience structuring sophisticated enterprise deals, including pricing, contracts, resource requirements, and engagement economics.

• Experience selling complex software, AI solutions, technical services, or research-driven solutions to large enterprise customers.

• Demonstrated ability to operate as a hands-on individual contributor while providing strategic leadership and direction from day one.

• Experience owning customer engagements beyond the sale, including implementation, delivery, stakeholder management, and ensuring contractual commitments are met.

• Strong technical aptitude and the ability to understand complex AI capabilities, engage credibly with technical stakeholders, and translate customer problems into executable solutions.

• Ability to work closely with research, engineering, and operations teams to scope engagements, align resources, and deliver against customer expectations.

• A builder's mindset: you take full ownership, operate independently, move quickly, and create structure where little exists.

• Exceptional executive presence, negotiation, communication, and relationship-building skills.

• Comfort operating in an ambiguous, fast-moving environment where individual ownership, commercial judgment, and results are essential.

We're particularly interested in candidates who have built and scaled enterprise GTM functions within AI, enterprise software, AI infrastructure, or technical services businesses, as well as commercial leaders who have helped large organizations adopt and implement AI at scale.

Relevant experience may include:

• Head of Enterprise Sales, VP of GTM, Chief Commercial Officer, or similar leadership roles at high-growth technology companies.

• Enterprise AI companies selling complex, high-value solutions to frontier AI labs, Fortune 500 companies, or sophisticated enterprise customers.

• AI implementation and transformation leaders at top management consulting firms (MBB) who have led enterprise AI strategy, deployment, and implementation initiatives, working directly with C-suite stakeholders and translating complex business challenges into technical solutions.

• AI infrastructure, technical services, or applied research businesses where commercial leaders own both deal structuring and customer delivery.

• Early-stage companies where the candidate personally generated pipeline, closed strategic accounts, established commercial processes, and built a sales organization.

• Experience managing large enterprise contracts, complex implementations, and long-term strategic customer relationships.

We particularly value candidates who have personally driven revenue, built executive-level relationships, and owned customer outcomes. This could include traditional enterprise sales leaders as well as consulting leaders who have demonstrated the ability to identify commercial opportunities, lead complex AI engagements, and drive successful enterprise implementations.