Jobs at Plot Technologies, Inc.

Design and craft core product experiences from concept through launch; evolve design systems and visual/interaction quality; prototype quickly; partner with engineers; conduct customer research and translate insights into product decisions; design AI-first workflows and help shape design culture.

Own full-cycle enterprise sales from prospecting to close. Source outbound pipeline using modern sales/data tooling, run discovery and product demos for marketing/social leaders, partner with founders and CS to close and expand deals, and maintain CRM hygiene and forecasting.

Support Plot's social channels by ideating, filming, editing, and posting short-form content for TikTok, Instagram, and X. Research trends, synthesize reports using Plot, and recommend partner podcasts/newsletters. Collaborate with Brand & Community and Growth leads to produce creative, on-camera content and daily social posts.

Own and harden Plot's core data platform: stabilize high-throughput ingestion, design read-optimized schemas and partitioning, separate transactional vs analytical workloads, ensure performant data access for dashboards and AI agents, write RFCs, and raise reliability and observability across teams.

Lead and scale Plot's B2B marketing function: build demand-generation programs, establish high-touch events, create thought leadership and content strategies, run ABM with sales, test new channels, and own pipeline metrics (MQLs, opportunities, revenue influence). Start as an individual contributor and grow into hiring and org building.

Build agentic, reasoning-driven systems on top of LLMs; own full-stack AI product features from prompt design to orchestration, tooling, monitoring, and UX. Prototype with design, run LLM evaluation and A/B tests, integrate emerging methods, and collaborate directly with founders and customers to deliver product-facing AI features.

Own and scale core data systems powering high-throughput ingestion, storage, analytics, and product surfaces. Stabilize write paths, design read-optimized models and partitioning strategies, separate transactional and analytical workloads, enable AI-native analytics, write RFCs, and raise reliability and performance standards across the team.