Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Lead the development and release of frontier AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelance subject-matter experts. Conduct hands-on evaluation review, maintain ecosystem relationships, present research to clients, and attend conferences.

Serve as the senior technical front line for frontier AI lab clients in the Bay Area. Lead technical discovery, RFPs, solution scoping, client meetings, events, and technical discussions with engineering and research teams. Build the Valley AI and security community, represent the company publicly, translate market signals into research and product strategy, and help establish the company’s regional presence. Partner with sales on technical wins while influencing AI security research, product direction, and local hiring.

Own full sales cycle for GenAI customers, engaging senior product, research, and safety stakeholders. Position and sell AI safety, red teaming, model evaluation, and post-training data services. Scope pre-sales, shape proposals with solutions teams, drive pricing and negotiations, and maintain accurate pipeline forecasting.

Lead the development and release of AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, verification, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelancers. The role also requires staying current with AI safety research, maintaining lab relationships, presenting work to clients, and attending conferences.

Analyze generative AI content infringements and develop adversarial prompts to identify model vulnerabilities across hate speech, misinformation, intellectual property, and other abuse areas. Manage multilingual datasets, investigate safety circumvention tactics, oversee projects and quality assurance, and collaborate with engineering, product, and policy teams to improve AI safety strategies.

Lead a multidisciplinary red teaming team to design and run adversarial tests, evaluate model risks, produce high-quality deliverables, and communicate findings to clients while improving methodologies and workflows.

Analyze content infringements and write adversarial prompts to find model vulnerabilities across LLMs, text-to-image/video, and agents. Manage datasets and projects end-to-end, investigate evasion tactics, collaborate with engineering, product, and policy teams, and promote knowledge sharing to improve model safety.