Sales Engineer

A sales engineer in B2B software usually pairs technical depth with customer-facing skill, running demos, scoping integrations and answering hard product questions during deals. A strong candidate can explain data pipelines and ad tech clearly to marketers and engineers alike, and can turn a prospect's buying process into a concrete setup plan. Comfort with APIs, CRM tools and account data helps, since the product scores accounts from buying signals. How it fits the AI era AI shifts much of the routine work here: demo setup, integration checks and first-pass technical answers can be drafted or automated, so the role leans more on judgment about what a customer actually needs. What stays human is trust building, reading a room, and deciding when a technical fit is real. The engineer becomes the person who translates model output into a credible plan. How it builds AI experience This role builds hands-on AI experience with signal scoring, account matching and ad targeting, which are core to an AI advertising platform. A candidate can prepare by learning how scoring models are evaluated, how data quality affects targeting, and how to explain limits honestly to buyers. Practicing demos of AI-driven tools and studying ad tech data flows would help. Worth showing API and integration fluency B2B ad tech knowledge Clear customer communication CRM and data tools This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role. About Vector An AI advertising platform for B2B marketers that scores target accounts from buying signals and shows ads to named buying-committee members. #J-18808-Ljbffr