Top Tech Jobs & Startup Jobs

Own and scale full-funnel paid acquisition across search, social, video, retargeting, and developer-focused platforms. Manage campaign strategy, budgets, targeting, bidding, creative and landing-page testing, attribution, and conversion measurement. Analyze cohort and funnel performance, improve CAC and payback, and communicate insights through reporting. Collaborate with creative, marketing, sales, lifecycle, data, and engineering teams to improve lead quality, signups, pipeline, and revenue.

Develop and execute top-of-funnel paid media campaigns across television, podcasts, out-of-home, streaming, sponsorships, and emerging channels. Own media planning, budgeting, buying, negotiations, vendor relationships, creative coordination, testing, and measurement. Evaluate brand awareness, consideration, reach, demand, and campaign impact through brand-lift studies, incrementality analysis, geographic testing, and media mix modeling. Communicate insights and recommendations to leadership while identifying high-impact audiences, markets, cultural moments, and emerging opportunities.

Build and operate ML platform infrastructure supporting researchers and product engineers. Responsibilities include designing distributed systems, data pipelines, observability tools, scheduling and orchestration infrastructure, and GPU fleet systems. The role partners closely with ML research, owns reliability and performance, improves developer experience, and ships platform primitives in a high-ownership environment.

Generate qualified pipeline through high-volume outbound prospecting, account research, stakeholder mapping, discovery conversations, and personalized multi-channel outreach. Partner with Account Executives on account strategies and opportunity handoffs, meet activity and qualified-meeting targets, represent Cursor’s product, share market intelligence, and help develop the company’s sales playbook.

Own the complete enterprise sales cycle for Cursor, from outbound prospecting through close. Build pipeline, acquire new logos, exceed revenue targets, develop executive and technical stakeholder relationships, guide product trials and rollouts, quantify ROI, execute sales strategies, analyze market trends, and provide customer feedback to influence the product roadmap.

Design and iterate task sets, rewards, and environments for coding agents. Analyze agent traces and evaluations to identify failure modes, build systems to surface recurring behaviors, and convert one-off solutions into reusable training infrastructure and high-quality datasets. Partner with research teams to validate that datasets teach intended capabilities. The role requires strong software engineering fundamentals and comfort with infrastructure, data, or distributed systems.

Own a portfolio of commercial SaaS customers, driving expansion, adoption, net revenue retention, and renewals. The role involves multi-threading with technical and product leaders, managing usage-based commitments, leading renewal negotiations, cross-selling platform capabilities, and developing account tiering strategies. The Account Executive will translate rapidly changing AI products, models, and pricing into customer value narratives while partnering with Product, Support, RevOps, and Sales Leadership.

Build AI-powered product quality infrastructure for capturing, synthesizing, routing, and acting on customer feedback. Develop bug intake and triage systems, dashboards, data pipelines, analytics tooling, and integrations with ticketing, payment, CRM, and data warehouse systems. Partner with support engineers and domain specialists to improve product quality and ship internal tools quickly.

Leads and scales a founding commercial sales team serving high-value digital-native businesses. Responsibilities include coaching account executives, creating repeatable high-velocity sales processes, establishing forecasting practices, partnering with RevOps and GTM leadership, coordinating cross-functional account handoffs, hiring and onboarding talent, and shaping strategy for a new business segment.

Build large-scale data systems for frontier coding-model pretraining across data quality, data platform, or web crawling. Responsibilities include developing high-throughput pipelines, training and deploying data-quality models, orchestrating reproducible datasets, improving crawl coverage and parsing, and hardening distributed infrastructure. The role requires independent end-to-end ownership, performance optimization, observability, experimentation, and close collaboration with research, training, acquisition, and engineering teams.