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

Owns AI product bets and core platform features from prototype through beta and go-to-market. Conducts user research, rapidly prototypes solutions, builds and evaluates LLM-based agents, defines quality standards, and partners with engineering on AI development tools and workflows. Uses analytics to guide decisions and collaborates with sales, customer success, design, and data science to drive adoption, pricing, launches, and product growth.

Owns AI product bets and core product features from research and prototyping through beta and go-to-market. The role leads user research, rapid experimentation, agent and evaluation design, AI software development workflows, product prioritization, adoption, pricing, launches, and growth. It partners closely with engineering, design, data science, sales, and customer success while applying data-driven judgment to product decisions.

Generate qualified sales opportunities through phone, email, LinkedIn, and other outreach channels. Research target accounts, identify decision-makers, tailor messaging, conduct initial qualification conversations, maintain accurate CRM records, manage follow-ups, and meet activity and pipeline goals. The role also involves testing messaging and refining prospecting processes directly with the Chief Revenue Officer in a fast-paced startup environment.

Own enterprise client relationships and advise brand, marketing, and insights teams on research and pre-testing programs. Guide research design, execution, interpretation, and actionable recommendations. Drive platform adoption, identify new use cases, provide product feedback, and partner with sales on pitches, renewals, and expansion. The role requires strong client communication, analytical reasoning, research knowledge, project management, and presentation skills.

Own enterprise client relationships and advise brand, marketing, and insights teams on research and pre-testing programs. Guide research design, execution, and interpretation; translate findings into actionable messaging and creative recommendations. Drive platform adoption, identify use cases, provide product feedback, and partner with sales on pitches, renewals, and expansion. Manage multiple client priorities while communicating complex research and quantitative insights clearly to nontechnical audiences.

Build and improve Swayable’s AI and analytics engine using Python, scientific computing, machine learning, and distributed systems. Develop scalable, high-performance software, optimize parallel computing architecture, productize AI and data analysis capabilities, and collaborate with engineers, data scientists, and researchers. The role also includes designing new features, maintaining testable code, mentoring junior engineers, documenting decisions, and providing technical feedback.

Own product marketing at the intersection of product, engineering, sales, and go-to-market. Responsibilities include translating technical innovations into sales enablement materials, managing product launches, developing onboarding and certification programs, maintaining the standard demo narrative, gathering field feedback, identifying expansion opportunities, and creating pilot-to-program conversion playbooks. The role requires strong storytelling, cross-functional collaboration, project management, competitive positioning, and B2B SaaS product marketing experience.

Lead enterprise account relationships to drive retention, growth, and expansion. Partner with Sales, Client Success, and Revenue Operations to identify opportunities, win pitches, negotiate contracts, ensure client satisfaction and product adoption, and inform product development based on market trends.

Conduct data science research advancing experimental and causal methodologies; develop robust tools and prototypes to analyze experimental data; improve core platform features; and communicate findings to internal teams and external stakeholders to drive insights and product improvements.

Conduct data science research on experimental methodologies and causal modeling, develop tools to analyze experimental data, prototype improvements to platform features, and communicate results to internal teams and external stakeholders to drive product and research decisions.