Expert Operations Manager

Responsibilities

As the Expert Operations Manager at Patronus AI, you will own the end-to-end lifecycle of the subject matter experts behind our simulation environments. The environments we deliver measure whether AI agents can perform real professional work, and their credibility depends on practicing experts defining what that work looks like and how it should be judged.

This is a highly autonomous role. You will own every stage of that lifecycle, from identifying the expertise a project requires through sourcing, vetting, onboarding, engaging, and paying the experts who deliver it. You will partner closely with our research and delivery teams to make sure every environment has the right expertise behind it, on the timeline the project demands.

Your work determines how quickly Patronus can stand up credible environments in new domains, and how much of the world’s professional expertise we can bring to bear on the next generation of frontier models.

In this role, you will:

• Own the expert lifecycle end to end, from sourcing and outreach through screening, contracting, onboarding, engagement, and retention.
• Design and run the vetting process that qualifies every expert before they work with our research team, and continuously improve it based on how well it predicts delivered quality.
• Build sourcing strategies suited to senior and licensed professionals, across registries, associations, alumni networks, referrals, and vendor partners.
• Partner with research and delivery leads to define the expertise each environment requires and match the right experts to each project.
• Manage day-to-day engagements with experts, including assigning work, reviewing submissions against quality standards, resolving blockers, and approving payment.
• Own the quality and incentive systems for the expert community, including scoring rubrics, peer review, bonuses, and ongoing calibration.
• Instrument and report on the funnel, tracking conversion, time in stage, cost per onboarded expert, responsiveness, and retention, and using that data to decide where to invest next.
• Turn recurring operational work into repeatable processes, documentation, and tooling that increase the number of experts supported per internal headcount.

Qualifications

"The number one qualification to succeed in this machine learning course is gumption” - John Lafferty, CS Professor at Yale

Above all, we look for an eagerness to learn, passion for research, creativity in problem solving and a proactive mindset. You are a great fit if you have a background in the following:

• Bachelor’s degree in Business, Operations, Economics, Engineering, or a related field, or equivalent practical experience.
• 4+ years in expert networks, AI data and evaluation companies, marketplace or talent operations, or professional services resourcing, with ownership of both throughput and quality.
• Proven track record of building an operational funnel from the ground up and instrumenting it, using data to identify and remove bottlenecks.
• Highly analytical, with experience defining KPIs, building dashboards, and making resourcing decisions from data.
• Excellent written and verbal communication, with the ability to engage credibly with senior professionals across unfamiliar domains.
• Comfortable operating in ambiguity and building structure where none exists, with a hands-on mentality and a strong bias toward action and automation.
• Experience working with contractors or licensed professionals, including contracting, onboarding, and payments, is a plus.
• Comfort using AI tools to do real operational work is a must.
• Good character, integrity, and respect for others!