/AI & Data Presales Expert / I

AI & Data Presales Expert / I

Poland - Warsawplvia direct
// Job Type
Full Time
// Salary
Not disclosed
// Posted
2 weeks ago

About the Role

The AI & Data Presales Expert leads the full presales lifecycle for data, analytics, and AI opportunities: from early qualification through discovery, solution shaping, proposal creation, and handover to delivery. The role combines strong client-facing skills, technical literacy in modern data/AI platforms, and the ability to craft compelling value cases and solution narratives. It requires close collaboration with Specialized Sales, Solution Architects, and SMEs to build winning proposals and guide customers toward clear, measurable outcomes. Key Responsibilities Opportunity Qualification & Deal Shaping - Assess opportunity fit, customer readiness, stakeholder landscape, decision process, risks, and next steps together with Specialized Sales. - Shape commercial options, scope boundaries, delivery models, and risk/assumption clarity. Customer Discovery & Requirements Definition - Prepare and lead discovery workshops and interviews with business and technical stakeholders. - Capture functional and non-functional requirements, constraints, success metrics, and KPIs. - Translate findings into a structured use-case backlog and MVP definition. Solution Narrative & Architecture Coordination - Build and maintain the solution storyline, including phased roadmap, trade-offs, and alternative options. - Coordinate Solution Architects and SMEs to define the solution approach, sizing inputs, delivery model, and risk/assumptions register. Presales Deliverables & Proposal Ownership - Produce high-quality presales artifacts: executive presentations, proposals/SoWs, RFP responses, and compliance matrices. - Ensure clarity, structure, and consistency across all written materials. - Drive internal reviews, bid cadence, and readiness checkpoints to ensure alignment between Sales and Architecture. Value Engineering & Business Case Development - Create and update ROI/TCO models, benefit hypotheses, and measurement plans. - Align value case with customer KPIs and strategic priorities.

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