Top Tech Jobs & Startup Jobs in Los Angeles, CA

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.