Cyber Security Analyst, Sales Engineering
- Compensation
- Not disclosed
- Location
- USA
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Security
- Posted
Skills
Must have
- 3+ years of experience in cybersecurity, with a proven track record in research analysis, threat intelligence, threat detection engineering, or threat hunting.
- Ability to collect, process, analyze, and interpret large and imperfect datasets to derive actionable insights, and to reach a conclusion you can defend under challenge.
- Proficiency in programming/scripting languages, with a default instinct to automate a repetitive problem rather than repeat it.
- Working knowledge of enterprise security controls - EDR, NGFW, WAF, CNAPP and cloud security, vulnerability scanners - and how each one actually mitigates risk in practice.
- Experience with network/security-related data analysis.
- Proficiency in SQL and TCP/IP network fundamentals.
- Comfort working directly with customers. You can hold technical ground with a skeptical security team and explain a finding clearly instead of hiding behind jargon.
- Strong team player with excellent collaboration skills, and experience managing multi-departmental interactions with cybersecurity professionals, engineering teams, and product managers.
- Self-directed, low-ego, and comfortable with ambiguity and the pace of a fast-growing startup.
Full description
Description
Zafran is actively looking for an experienced Cyber Security Analyst to join the Sales Engineering organization at our dynamic cybersecurity startup. We are looking for an individual who thrives on unraveling the intricacies of computing environments and attackers' techniques, and who turns that understanding into tooling, data, and evidence our customers can act on. This role sits with the field rather than in R&D: you will research live customer and partner environments for risk, own threat intelligence for the go-to-market team, and build the tooling that makes every evaluation faster.
About Zafran:Our Mission: To stop the exploitation of vulnerabilities, everywhere.
What makes us different: In a world where AI-enabled attackers weaponize vulnerabilities within minutes, the old scan-and-patch-everything model no longer holds. Zafran's Exposure Graph continuously maps every vulnerability across your hybrid environment, chains exploitability through real attack paths and proves 90% of "critical" vulnerabilities can't actually reach you. It then neutralizes the real 10% using your compensating controls and safely remediates only where it matters.
Who’s behind us: Zafran is backed by Menlo Ventures, Sequoia Capital, Cyberstarts, and a deep belief that cybersecurity should move as fast as attackers do. We’re one of the fastest-growing companies in the industry, scaling to meet demand from the world’s most advanced, security-obsessed organizations.
What you will do:
- Build and maintain the tooling the field runs on - scripts, automations, and data utilities that shorten POV setup and remove manual work from the Sales Engineering team.
- Partner with Sales Engineers to stand up Proofs of Value: tenant configuration, integration scoping, data validation, and instrumentation of success criteria.
- Bring in customer data. Connect the customer's existing security stack, validate coverage and data quality, and resolve the ingestion issues that quietly stall evaluations.
- Research customer and partner environments for risk. Analyze vulnerability posture, deployed security controls, and exposure paths to separate what is genuinely exploitable from what is already mitigated by controls the customer already owns.
- Own threat intelligence for the go-to-market organization. Track emerging CVEs and active exploitation campaigns, drive rapid response when something breaks in the news, and arm the field with a credible answer within hours.
- Present findings directly to customer security teams, and back up Sales Engineers when a conversation needs research depth.
- Collaborate with Product, R&D, and Research - feeding field findings, data gaps, and detection misses back with the specifics needed to act on them, and validating new mitigation logic against real customer data.