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Mercor is an AI data company that organizes human intelligence to power the AI economy. The company operates a platform where millions of domain experts train frontier AI models, and serves Fortune 500 companies through Mercor Enterprise. As a Deployment Strategist, you'll operate at the intersection of Product, Engineering, Operations, and GTM, working directly with leading AI labs and internal teams.
You'll own the technical scoping of complex AI data projects during the sales process, translating ambiguous customer requests into sized, deliverable initiatives. This includes defining technical requirements, breaking down engineering effort, and identifying ROI for each project. You'll drive account growth by working with AI researchers and GTM leads to formulate growth plans, leveraging Mercor's evaluation infrastructure and data inventory to generate new demand.
Key responsibilities include leading customer implementations by assembling the right solution, composing teams and resources, and coordinating across Product, Engineering, GTM, and customer stakeholders. You'll own the roadmap for customer integrations with external platforms and data systems, expanding integration surfaces to unlock new revenue. You'll also lead delivery incident response and root-cause analysis, triaging technical blockers and tracking corrective actions to ensure reliability.
You'll identify recurring customer needs and translate them into product requirements, shaping the platform's evolution. This role requires 2+ years in Product Management, Technical Program Management, Solutions Engineering, Forward Deployed Engineering, or Implementation Consulting. You need technical fluency with coding agents, SQL, and Python; ability to break down large engineering problems; and comfort holding technical conversations with AI researchers and engineers. Strong project management, cross-functional communication, and systems thinking are essential. You should thrive in ambiguous environments, demonstrate excellent ownership, and balance revenue upside against delivery costs.
