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

Build and lead the outbound sales and partnerships function for a consumer technology platform. Own prospecting, pitching, deal negotiation, closing, partner launch, and referral growth. Use multichannel outreach to sign notable individuals in entertainment, music, or sports, negotiate commercial agreements, and coordinate initial experiences. The role begins as a hands-on individual contributor and may develop into team leadership. Requires domestic travel at least monthly and is based in San Francisco.

Own full-cycle recruiting for business, operations, and go-to-market roles, from sourcing through offer acceptance. Build proactive talent pipelines, partner with senior leaders to define candidate profiles, run structured interviews, improve hiring tools and standards, and use funnel metrics to optimize recruiting processes. The role requires experience across agency and in-house recruiting, hiring from selective talent pools, and recruiting in high-growth startup environments. This is an on-site position five days per week in San Francisco.

Own the outbound sales funnel by making daily cold calls to B2B software decision-makers, qualifying prospects, and scheduling attended meetings. Partner with senior sales leaders on first meetings, messaging, objection handling, and outbound process development. Use AI tools and automation for prospecting and sequencing, attend local events, and contribute to building the company’s sales approach while meeting monthly quotas.

Own customer implementations from sales handoff through go-live, serving as the technical point of contact. Lead discovery calls, product demos, configuration, data loading, training, troubleshooting, project coordination, and risk management. Partner with sales, engineering, product teams, and third-party collaborators to resolve issues and capture feedback. Develop scalable onboarding workflows, documentation, automation, templates, and metrics while identifying retention and expansion opportunities.

Handle significant commercial and real estate disputes for business clients, including motion practice, discovery, depositions, court appearances, and developing trial experience. The role involves increasing ownership of matters, building client relationships, pursuing new business, and progressing toward lead attorney responsibilities.

Design, build, and release full-stack application features; solve large-scale messy data problems; contribute to AI and LLM capabilities; influence early product and technical decisions; and work directly with business customers to deliver solutions.

Build and launch production AI services, including agent-style workflows and retrieval pipelines, for external business customers. Design data models and scalable pipelines, own products from concept through launch, and collaborate with commercial teams and customers. Use customer feedback to improve the platform rapidly. The role requires production LLM experience, startup or zero-to-one ownership, strong Python or equivalent programming skills, database design knowledge, and understanding of distributed systems.

Own client-facing projects from scoping through completion, lead cross-functional specialist teams, collaborate on research, manage client relationships, and drive company-wide operational initiatives. The role requires strong communication, stakeholder management, high agency, and experience testing systems for weaknesses through security testing, red-teaming, trust and safety, or similar work. This is an on-site role in San Francisco with a broad scope suited to an early team member.

Build and ship AI-driven automation features across backend and user-facing interfaces. Develop production LLM workflows, evaluation frameworks, safety guardrails, contextual data ingestion and indexing, and AI-assisted development tools. Collaborate with internal users to turn ambiguous problems into reliable software and establish engineering patterns for the wider team.

Build production recommendation, scoring, optimization, and reinforcement-learning systems that adjust advertising spend, budgets, and campaign status. Design feedback loops and multi-agent reasoning systems using live results and shared context. Own decision quality and financial outcomes while applying statistics, A/B testing, and advertising optimization concepts such as pacing, budget allocation, ROAS, and CPA targets.