Sales Engineer (AI)

Location: 100% remote within the Central or East Coast United States; travel required approximately 25–30%.

Company

Provides data quality, data enrichment, location intelligence, and AI-driven software for enterprise customers.

What you will do

• Support the full sales process through technical and business-value discovery with customers.
• Deliver online and in-person product presentations, custom demonstrations, workshops, proofs of concept, pilots, and assisted trials.
• Assess customer needs using SAP and product expertise, then demonstrate solution value to technical and operational stakeholders.
• Build custom solutions across Databricks, Snowflake, AWS, Azure, and GCP using APIs, SDKs, MCPs, and agents.
• Advise customers on cloud modernization, AI-driven initiatives, and scalable data strategies.
• Create reusable demonstrations, documentation, and pre-sales assets.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related technical field.
• At least 2 years of experience with SAP, including ECC, S/4HANA, Fiori, SAP MDG, or BTP.
• Experience communicating with, presenting to, and influencing technical, operational, and C-suite stakeholders.
• Demonstrable experience with generative AI and MCP servers, including LLM fundamentals, RAG, prompting, fine-tuning trade-offs, and hallucination risks.
• Hands-on experience with cloud-native infrastructure and SaaS architecture, including AWS.
• Ability to work remotely from the Central or East Coast United States and travel approximately 25–30%.

Nice to have

• Experience with data enrichment, location intelligence, data quality, data governance, data integration, SAP automation, or MDM.
• Experience developing solutions with Scala, Python, Java, or Spark in Databricks environments.
• Experience evaluating AI vendor claims and identifying practical customer applications for AI.

Culture & Benefits

• Fully remote work within the specified US region.
• Work at the intersection of AI, data integrity, data quality, and location intelligence.
• Collaboration with sales, customers, prospects, and partners on strategic transformation programs.