Enterprise Security Solutions Engineer (Remote)
Clearly AI, Inc.
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Job summary
Clearly AI, Inc. is seeking a seasoned security-focused Solutions Engineer/Sales Engineer to lead technical discovery and demos for Fortune 500–level buyers.
You will demonstrate how threat modeling, privacy, and vendor risk reviews are executed, and you will translate customer requirements into concrete proofs of value. As a key technical voice alongside Sales, you will address architecture, data residency, and deployment considerations, while building repeatable demos and templates to
Qualifications
- 5+ years either running security and privacy reviews for large enterprises, or in a sales engineering, solutions architecture, or technical pre-sales role selling to security teams
- Command of enterprise security architecture: tenancy and data isolation, data residency, AI governance
- Ability to speak the language of security practitioners (STRIDE, DPIA, TPRM, CVE, SSDLC)
- Experience running a multi-week technical engagement to a deadline without it drifting
- Familiarity with Jira, ServiceNow, GitHub, Confluence, or OneTrust, and how review workflows live inside them
- Clear writing. Success criteria, test plans, and readouts are the deliverables here
Responsibilities
- Own technical discovery and demos tailored to each prospect's use case
- Develop and run proofs of value against written success criteria
- Navigate architecture questions like tenancy, data isolation, and deployment patterns in customer discussions
- Own the reusable demo environments, POV templates, and technical answers for the team to leverage
Skills
Tools
Job description
Clearly AI, Inc. is seeking a seasoned security-focused Solutions Engineer/Sales Engineer to lead technical discovery and demos for Fortune 500–level buyers.
You will demonstrate how threat modeling, privacy, and vendor risk reviews are executed, and you will translate customer requirements into concrete proofs of value. As a key technical voice alongside Sales, you will address architecture, data residency, and deployment considerations, while building repeatable demos and templates to
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