Founding Technical Program Manager

Description

The company is a superintelligence data research firm that builds RL environments to train AI systems that are more capable and better aligned. Model behavior depends largely on the reward signals used in training, and the company works on those training objectives, both for today's models and for future, more capable ones.

The company has built RL environments for several frontier labs over the past year and has $16M in seed funding led by a16z. Its founders previously worked on Anthropic's data team, building data infrastructure and datasets used for Claude.

This is the company's first Technical Program Manager hire. Frontier labs are choosing which RL environment partners to trust with their training runs, and the relationships built now will shape much of the company's direction. Until now, leadership has managed these relationships alongside other work. This role makes one person fully responsible for them.

This is a founding role with wide ownership. You will own communication with lab customers across selling, delivery, scope expansion and contract negotiation, while the platform team owns technical delivery. You will have a real voice in which labs to pursue, how work is priced, and what gets built next. You will help build the go-to-market playbook and may later get to grow the team.

You will report directly to a co-founder and work onsite in San Francisco with leadership, the capabilities team and the platform team.

Success means projects ship on timelines both sides trust, and the relationships you own grow into larger engagements.

Responsibilities

• Be the main contact for frontier lab customers, move each relationship forward and grow accounts into bigger engagements.
• With leadership, decide which labs and markets to pursue and where to focus as the RL environment market shifts.
• Run the sales cycle: send samples, learn what each lab needs, and turn early conversations into scoped projects.
• Shape pricing and packaging, and negotiate contracts with the co-founders.
• Turn customer feedback into focus areas and priorities through regular feedback loops.
• Keep delivery on schedule: set realistic timelines, review purchase orders, and work with the platform team so nothing falls between teams.
• Represent the company publicly through writing, events and the AI community.
• Build the go-to-market function from the ground up, including how the company sells, scopes, contracts and delivers, and the playbooks that make these repeatable.

Requirements

• A background in building something from scratch, such as at an early-stage startup, as a founder, or in venture capital.
• A computer science or closely related technical degree, or prior software engineering experience.
• Customer-facing experience, for example as a forward deployed engineer, in customer success or operations, as a product manager, or in venture capital.
• At least 2 years of relevant experience.
• Experience negotiating commercial terms such as customer contracts, pricing or investment deals.
• Comfort working with senior technical stakeholders and the follow-through to keep many relationships moving at once. You can push back on unrealistic requests, share bad news early and make sure nothing is dropped.
• Experience with LLM training or post-training is strongly preferred.
• Experience at a frontier AI lab, neo lab or neocloud is strongly preferred.
• Experience at a company known for strong customer support is preferred.
• Familiarity with RL environments, evals, benchmarks or post-training data such as RLHF and RLVR is preferred.
• Public writing, such as a blog, newsletter or essays, or an active social media presence, is a plus.
• You may be a good fit if you started as a software engineer or forward deployed engineer and later took on roles that combine technical depth with owning customer outcomes.
• You may be a good fit if you founded a company and sold to technical buyers yourself.
• You may be a good fit if you have run engagements for frontier lab customers at an AI data, evals or RL environment company.

Conditions

Onsite in San Francisco.

Reports directly to a co-founder.

The company values diverse perspectives and encourages applications even if you do not meet every listed qualification.

Benefits

• Competitive cash and equity compensation.
• Ownership and autonomy in a fast-moving startup.
• Opportunity to work with top machine learning engineers.
• Health, vision and dental coverage.
• 401(k) match.
• Lunch provided daily and a weekly snack order.