Sales Engineer / Solutions Consultant
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- Turn customer problems into credible technical architectures
- Prove the technical win safely
- Convert technical wins into business value and durable adoption
Benchmark: Salesforce Pre-Sales Solution Engineering + Datadog Enterprise Sales Engineering + OpenAI Applied AI Architecture (current Sep 2026) Market refresh: deep discovery, business/technical requirements, architecture/API/integration design, tailored demos/POVs, measurable success criteria, security/compliance, value/ROI, executive storytelling, technical champions, deal orchestration and feedback-to-product.
Who’s Hiring Right Now
US openings posted in the last 7 days at OpenAI — this role’s own benchmark employers — refreshed daily, as of 2026-11-01. Pulled directly from each company’s public job board; not exhaustive, and postings close fast — worth confirming the details on the employer’s own site before applying.
Turn customer problems into credible technical architectures
Discovery, qualification + success criteria
Coverage: Technical Sales & Solution Engineering / Product Discovery
Solution architecture, APIs + integration
Coverage: Systems Architecture / APIs / Integration Strategy
Prove the technical win safely
Tailored demos, prototypes + proof of value
Coverage: Technical Sales / Prototyping / AI Solutions
Security, identity + production readiness
Coverage: IAM / Security / Reliability
Convert technical wins into business value and durable adoption
Business value, ROI + executive narrative
Coverage: Business Cases & Unit Economics / Executive Communication
Technical champions + deal/product orchestration
Coverage: Stakeholder Management / Product Feedback / Adoption
Role-Readiness Proof / Capstone
Own an enterprise technical sales cycle end to end: conduct discovery and document business/technical requirements and decision criteria; produce a target architecture with API/integration, data, identity and security views; build a tailored demo and proof-of-value plan with measurable success criteria; prototype one integration/AI workflow and evaluate it; quantify business value/ROI; run a technical workshop and executive readout; create the mutual action plan, risk/production-readiness checklist and handoff package for implementation/adoption.
Proof Rubric
- Demonstrate discovery depth and requirement traceability
- defend architecture and integration tradeoffs
- prove the solution with a working demo/POV and explicit success criteria
- address identity, security, reliability and compliance
- quantify customer value rather than feature activity
- influence technical and executive stakeholders
- cultivate champions
- surface risks early
- capture product feedback
- and show a credible path from technical win to production adoption