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The Product Marketing Manager will position and launch Relevance AI's Agent platform, translating complex capabilities into value stories, executing go-to-market strategies, and collaborating with cross-functional teams to drive customer adoption.

The Product Marketing Manager will position and launch Relevance AI's enterprise agent platform, create value stories, and drive activation and growth through collaborative go-to-market strategies.

Lead Americas implementation team to turn enterprise AI use cases into measurable outcomes. Own pre‑sale trial planning and post‑sale end‑to‑end delivery, building processes, playbooks, capacity planning, and value tracking. Collaborate with product, solutions engineering, and account teams to drive adoption, change management, ROI measurement, and executive stakeholder engagement.

Lead and scale the San Francisco-based US sales team for a B2B SaaS AI platform. Drive pipeline management, forecast discipline, coaching, deal inspection, hiring/onboarding of AEs, and translate market feedback into repeatable GTM behaviors while fostering in-person team accountability.

Own and evolve the AI-native platform and developer experience: build CI/CD, build/test/deploy loops, agent-safe sandboxes, cloud infra and cost controls, SLOs and observability, incident response, and platform capabilities that multiply engineering productivity across teams.

Lead technical direction for AI-native agent products, solve high-leverage engineering problems, improve reliability and evaluation, partner with product and customer teams, mentor engineers, and ship production-grade autonomous agent features rapidly.

Build and ship AI-native, agentic products end-to-end: design LLM-powered workflows, prototype with frontier models, collaborate with product/design/customers, ensure reliability through continuous shipping and on-call ownership, mentor engineers, and iterate based on customer feedback to scale intelligent agents into production.

Lead a 4–8 person AI-native engineering team to deliver production agent orchestration features. Coach engineers on product thinking, agentic workflows, and eval practices; remain hands-on in code, ensure quality and reliability, run postmortems, and hire top talent.

Partner with customers to identify high‑value AI agent use cases, scope and lead end‑to‑end deployments, drive adoption and change management, measure ROI and scale successful automations while aligning executives, product, and engineering.

Own a portfolio of enterprise customers post-implementation to drive adoption, retention, and expansion of Relevance AI’s agentic platform. Act as strategic lead, build executive and champion relationships, identify new use cases, collaborate with technical and sales teams, and measure success via NRR/NDR.