Jobs at Culture Amp

Own enterprise account expansion sales by identifying upgrade and add-on opportunities, building executive relationships, delivering tailored product demonstrations, developing ROI-based business cases, managing complex sales cycles, and closing deals. Maintain pipeline and forecasting data in Salesforce while collaborating with Customer Success, Legal, Procurement, Security, Solution Consulting, and People Science teams to achieve client quotas.

Research target accounts, create personalized outreach, contact prospects by phone, email, and social tools, qualify leads, and book meetings with Sales Executives. The role serves as the first point of contact for potential customers and requires outbound sales experience, cold-calling confidence, strong communication, storytelling, collaboration, and openness to coaching. This is a hybrid position requiring two days per week in the Richmond office.

Designs, automates, and operates corporate identity, endpoint, workplace, cloud, network, and enterprise AI infrastructure. Owns Okta administration, identity lifecycle automation, Jamf Pro and macOS fleet management, infrastructure-as-code, observability, incident escalation, root-cause analysis, security, and reliability improvements. Provides senior technical support, documents recovery procedures, mentors colleagues, and governs enterprise AI platforms and integrations.

The Chief People Officer will lead Culture Amp’s global People Experience function across four countries, overseeing performance, engagement, compensation, talent acquisition, capability, compliance, organization design, and executive advising. The role also requires customer-facing market credibility, commercial partnership with Sales and Customer Experience, hands-on leadership of company-wide AI adoption and governance, and using Culture Amp as Customer Zero to influence product direction.

Build Culture Amp’s internal Agent Hub from the ground up, defining architecture, orchestration, MCP integrations, identity, knowledge retrieval, governance, evaluation, observability, and secure production operations. Develop autonomous agents and workflows, establish reusable engineering patterns and guardrails, solve ambiguous business problems, and coach teams on adopting AI-enabled systems safely and effectively.

Design and ship agentic AI features: build stateful multi-turn conversational systems, memory and context graphs, RAG and hybrid search, data pipelines and integrations, production LLM evaluation and observability, prompt engineering, safety guardrails, and partner with product and people science to deliver scalable, responsible AI in production.