Pre-Sales Program Lead, Forward Deployed Engineering

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

We're looking for our first Pre-Sales Program Lead to build the programs that take this team from opportunity to a signed contract. Your job will be to build the pipeline qualification and management mechanisms that keep quality opportunities flowing, the prioritization heuristics that decide where a capacity-constrained team places its bets across commercial, research, and mission-oriented deals, the pursuit-to-signature process (including the legal and finance ways of working) that gets contracts signed quickly and cleanly, and the partner coordination motions that determine when we pass an opportunity to a partner, when we team, and how we run subcontract or co-delivery pursuits well.

This is a foundational role; you'll be the first hire in this function, operating with high autonomy and in direct partnership with Forward Deployed Engineering leadership, with room for the role to grow as the function does. You'll work hand in glove with a Post-Sale Program Lead counterpart who owns delivery from signature onward. Together you'll define the handoff that connects your two halves of the engagement lifecycle. The right person finds energy in exactly this: a business with more demand than it can serve, and no machine yet for choosing well and closing fast.

Key responsibilities

Minimum qualifications

• Design, pilot and refine the pre-sales programs that run Forward Deployed Engineering's pipeline: how opportunities are generated, qualified, routed, pursued, and won across a high-velocity portfolio
• Own the prioritization heuristics that shape the portfolio, making deliberate trade-offs across commercial, research, and mission-oriented engagements and making those trade-offs legible to leadership
• Lead the most complex and high-stakes pre-sales pursuits personally — the ones where deal size, organizational complexity, or strategic sensitivity puts a senior operator in the room — while simultaneously building the programs that let a growing team handle everything else.
• Own definition of the pursuit-to-signature process: scoping, proposal development, approvals, and the legal and finance workflows that get contracts signed without cutting corners
• Build the partner coordination motions for pre-sales: when to hand an opportunity to a partner, when to team, and how to run subcontract or co-delivery pursuits with tight management
• Define the process for handing off deals from sales to delivery, working closely with the Post-Sale Programs Lead so signed engagements arrive with what delivery teams need to start fast
• Stand up the metrics, dashboards, and reporting that measure pipeline health, conversion, cycle time, and portfolio mix and use them to drive continuous improvement
• Codify how the team pursues work into playbooks and self-service programs that let a growing organization run without bottlenecking on individual people
• Build Claude into proposals, deal qualification, and pipeline tracking, setting the bar for what AI-native looks like.
• Partner across Sales, Partnerships, Legal, Finance, and Product to keep Forward Deployed Engineering's pre-sales interfaces with the rest of the business clean and predictable
• Have built or scaled the pre-sales side of a services or delivery business — professional services, consulting, solutions or field engineering, or similar — owning qualification, prioritization, and forecasting across a portfolio of concurrent pursuits
• Bring enough technical fluency to scope and defend AI and software services work with engineering leaders and technical buyers, without being the one who builds it
• Have taken complex deals through contracting, working with legal, finance, and procurement stakeholders to get agreements signed
• Have designed program, playbooks, or cadences that other people actually adopted and ran — not only documented
• Bring a strong analytical toolkit: you're fluent working with data, have stood up metrics and reporting from scratch, and use them to drive decisions
• Communicate clearly and credibly with audiences from engineers to executives, and can influence without authority across functions
• Work effectively in high-ambiguity environments and are comfortable building where no process exists yet
• Are excited about Anthropic's mission to develop AI that is safe and beneficial

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

• Experience with partner-involved deal motions, including subcontracting, co-delivery, teaming, or channel handoffs
• Have been the first programs or operations hire, or built such a function from scratch, at a company that scaled significantly during your tenure
• Have hired, developed, and led programs or operations teams
• Experience in AI or technical professional services, with enough technical fluency to reason about what modern AI products make possible

$270,000—$365,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.