Jobs at Surge AI

Manage corporate filings, legal records, deadlines, requests, budgets, invoices, vendors, and legal technology. Improve legal workflows, document processes, track obligations, and support attorneys while maintaining confidentiality and organization in a fast-moving environment.

Provide legal guidance on US and EU/UK data privacy, AI-related intellectual property, copyright, trademarks, data ownership, and cross-border transfers. Build privacy compliance programs, manage filings and inquiries, monitor evolving AI legislation and litigation, negotiate IP and data terms, partner with technical and business teams, manage outside counsel, and create practical legal guidance.

Corporate Counsel will manage customer and vendor agreements, review and negotiate contracts, advise Business Development and Growth teams, and develop legal forms, templates, and playbooks. The role partners with specialized counsel on IP, data privacy, and labor matters while addressing broader corporate and commercial questions. Candidates should bring strong commercial contract drafting, practical risk judgment, business-minded communication, and the ability to manage high-volume work independently in a technology, SaaS, data, or services environment.

Recruit experts for a global distributed workforce supporting frontier AI model development. Responsibilities include discovering unconventional talent channels, engaging skeptical domain experts, guiding candidates through assessments and onboarding, analyzing funnel quality, creating repeatable recruiting processes, and eventually building a recruiting team.

Lead end-to-end red-teaming campaigns against frontier AI models by defining threat models, designing attack scenarios and taxonomies, coordinating operators, and producing executive risk reports. Establish recurring testing cadences, track exploit families, measure severity and user harm, maintain dashboards, and partner with research, product, and operations teams to validate fixes and run regression tests.

Partner with AI labs to improve frontier models by designing targeted data collection workflows, analyzing experimental results, and implementing quality controls. The role involves evaluating model behavior, reducing bias, supporting model safety and alignment, and translating technical findings into actionable insights for AI researchers and customers. Python is used for data analysis, pipeline development, and workflow prototyping.

Conduct full-cycle recruiting for technical and non-technical roles, including sourcing, screening, scheduling, candidate closing, and offer coordination. Own searches from intake through close, source candidates creatively, partner directly with hiring managers, assess market fit, manage multiple searches with urgency, and improve recruiting processes. Technical recruiting experience is a plus, while strong writing, autonomy, and judgment are essential.

Source exceptional candidates across engineering, research, product, and partnerships. Build pipelines for difficult searches, map talent markets, write personalized outreach, conduct initial conversations, and deliver qualified candidates to recruiters. Advise hiring managers on market realities and develop new sourcing channels when standard approaches are ineffective.

Owns company-wide security across product, infrastructure, corporate systems, and IT. Responsibilities include fixing authentication and authorization issues, managing keys and secrets, hardening internal tools, improving permissions, contributing to backend engineering, and leading security reviews, incident response, and security tooling. This hands-on role requires broad security expertise, strong software engineering ability, and comfort working in an ambiguous early-stage startup environment.

Own end-to-end growth across contributor acquisition, reactivation, retention, and platform engagement. Lead workforce recruiting, channel experimentation, marketing and partnership initiatives, and cross-functional projects. Use data to identify opportunities, build models, run experiments, and scale effective tactics. The role requires AI/LLM familiarity, paid and organic campaign experience, strong communication, comfort with ambiguity, ownership, and senior-level execution.

Drives growth by identifying strategic partnerships with enterprise AI and machine learning companies. Develops business development strategies, builds relationships with senior decision-makers, negotiates complex deals, and collaborates with internal teams to implement partnerships. Requires strong AI/ML industry knowledge, executive communication skills, strategic thinking, and adaptability in a fast-paced startup environment.

Leads cross-functional programs that improve products, customer support, and value delivery. Owns execution, coordinates engineering and operations teams, establishes scalable processes, uses data-driven insights to improve customer models, scopes and sequences major initiatives, and communicates progress to stakeholders. The role requires program management experience, strong communication and influence skills, comfort with ambiguity, rapid execution in scaling environments, and interest in AI systems.

Oversee product operations from planning through delivery, coordinating product, engineering, and operations teams. Track and optimize performance metrics, improve operational processes, manage product communications, resolve delivery roadblocks, and use data-driven insights to support scalable product execution and continuous improvement. Interest in AI/ML systems is beneficial but not required.

Build scalable data pipelines, automation workflows, internal tools, and AI-powered quality-control systems. Lead data collection projects for frontier AI labs, establish quality frameworks, improve customer support processes, and manage cross-functional execution. Collaborate with technical and non-technical stakeholders to solve ambiguous operational challenges and deliver datasets and systems that improve advanced AI models.

Own the direction and execution of critical AI development products. Build AI-assisted annotation tools, data exploration and visualization interfaces, RLHF workflow products, large-scale data processing systems, and tools for communicating complex instructions. Make autonomous technical and product decisions, lead ambiguous projects, ship rapidly, and collaborate with engineering and research leaders to support AI training and evaluation.

Leads cross-functional AI programs spanning customer support, product, operations, engineering, and business development. Responsibilities include building scalable systems and processes, coordinating feature implementation, managing multiple projects, setting timelines, driving execution, and aligning technical and non-technical stakeholders. The role suits an early-career professional comfortable with ambiguity, competing priorities, influence without authority, and rapid organizational growth.

Manage end-to-end data operations, including collection, processing, delivery, pipeline optimization, and data quality monitoring. Collaborate with engineering, product, and operations teams to improve data workflows, identify inefficiencies, and implement scalable solutions. Analyze data to provide actionable insights for decision-making and AI model development while communicating technical issues to non-technical stakeholders.

Manage end-to-end product operations, coordinating product, engineering, and operations teams to ensure efficient feature and solution delivery. Track and optimize performance metrics, resolve operational roadblocks, manage product-update communications, and use data-driven insights to improve processes and support product success. The role requires strong analytical, communication, organizational, and continuous-improvement skills in a fast-paced, ambiguous environment.

Leads cross-functional technical programs across engineering, operations, product, customer support, and business development. Establishes scalable systems and processes, coordinates feature implementation, manages multiple concurrent projects, sets timelines, and drives teams toward deadlines. The role requires strong stakeholder communication, influence without authority, comfort with ambiguity, and the ability to balance competing priorities in a rapidly scaling AI-focused company.

Own the full lifecycle marketing program for a contributor workforce, including onboarding, activation, engagement, retention, and reactivation. Lead email strategy, segmentation, deliverability, testing, copywriting, and performance analysis. Run paid marketing experiments, productize marketing playbooks, and apply UX sensibility to communications. Collaborate with product, design, operations, and growth teams on positioning, messaging, launches, and platform improvements.