Solution Engineer

Job Description

Solution Engineer

This is a hands-on technical role . You’ll build and adapt solutions across cloud, data, AI, geospatial, APIs, and integrations —including taking existing reference solutions and tailoring them to new customers, geographies, and use cases without relying on Engineering for every build.

This role is revenue-focused from day one , with responsibility for pipeline contribution, technical wins, and supporting the path from initial discovery through evaluation and production.

Key Responsibilities

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• Drive Revenue: Partner with Account Executives to build pipeline, advance qualified opportunities, and contribute to technical wins and closed revenue.
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• Identify & Qualify Opportunities: Uncover new use cases, technical entry points, and expansion opportunities while assessing business value, technical feasibility, and path to purchase.
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• Lead Technical Discovery: Engage executives, architects, data, AI, cloud, GIS, security, and engineering stakeholders to understand business needs and define solution requirements.
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• Design & Build Solutions: Create and adapt technical solutions, demonstrations, evaluations, and PoCs using Xoople Earth data across customer workflows.
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• Own the Technical Sales Process: Develop technical win strategies, address risks and objections, build technical champions, and establish clear success criteria and production paths.
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• Build Partner Integrations: Develop reference solutions and integrations across Microsoft Azure, Fabric, Foundry, Databricks, and Esri , supporting co-sell and partner engagements.
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• Apply Hands-On Technical Expertise: Work with Python, SQL, REST APIs, Git, notebooks, Spark, Delta Lake, AI/ML, RAG, vector search, and agentic workflows .
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• Ensure Production Readiness: Evaluate scalability, security, data quality, reliability, and integration complexity to ensure PoCs demonstrate real production value.
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Education & Experience

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• 7+ years of experience in Solution Engineering, Sales Engineering, Technical Pre-Sales, Cloud/Data Architecture, Data Engineering, Geospatial Analytics, or a similar enterprise technical role.
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• Strong hands-on Python and SQL skills, with experience building data pipelines and analytical solutions using geospatial data.
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• Working expertise across Microsoft Azure, Microsoft Fabric, Microsoft Foundry, and Databricks .
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• Experience building AI agents or agentic workflows using Microsoft or Databricks technologies and enterprise data.
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• Experience with enterprise geospatial platforms , ideally including Esri ArcGIS .
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• Background working within the Microsoft or Databricks ecosystem , either as a vendor or technology partner.
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• Experience with structured enterprise qualification methodologies such as MEDDPICC or Command of the Message.
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• Ability to demonstrate technical expertise through a hands-on interview exercise , including building and presenting a solution using the Xoople API.
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Candidates complete a technical exercise as part of the interview process. Finalists may be asked to build and present a working demonstration against the live Xoople API from a customer scenario, and to explain the production path behind it

40% to 50% customer-facing travel, in the room rather than on a call