Responsibilities
- Engage customers on security-related products, architectures, and risk topics across the Veeam Data Platform (VDP).
- Run readiness checks and lead data modeling to validate solution design and accelerate decisions.
- Monitor attack surfaces and vulnerabilities (including DRMM scoring), track telemetry or recurring inspection signals, report trends, and capture potential health checks.
- Validate designs to de-risk adoption and accelerate time to value.
- Identify and articulate expansion opportunities; review consumption trends and schedule checkpoint reviews (with or without AE coordination).
- Engage CISO/CIO stakeholders for risk, status, and opportunity discussions; synthesize inputs from account health and CSE-led QBRs.
- Support AEs on security- and AI-driven expansion motions; influence roadmap priorities with CSE counterparts.
- Operate as a pooled resource covering Enterprise and Commercial-Named accounts (generally $100K+ ARR), typically at a 1 Security Success Engineer to 6–8 CSE coverage ratio.
Requirements
- 5+ years of experience in engineering or architecting cybersecurity, data security, or AI/ML-driven platforms (e.g., Security Engineer/Architect, Cloud Solution Architect, MLOps/ML Engineer, AI Security Engineer).
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or a related technical field.
- Relevant certifications (e.g., CompTIA Security+, CISSP, CISM, or equivalent).
- Deep expertise in data security and governance, including DSPM and DLP, with demonstrated experience securing data across cloud, SaaS, and hybrid environments.
- Hands-on experience with AI security, governance, or emerging AI platforms, including Securiti AI or similar solutions (e.g., AI-SPM, data privacy automation, model governance, or AI risk management frameworks).
- Working knowledge of AI/ML architectures and model lifecycles, including training data pipelines, model deployment, inference controls, and associated security risks (e.g., prompt injection, data leakage, adversarial inputs).
- Experience with AI/data observability, telemetry, and monitoring across both traditional systems and AI-driven workloads.
- Demonstrated ability to engage CISO/CIO/CDO stakeholders on AI risk, data governance, resilience, and enterprise AI adoption strategies.
- Hands-on experience with solution design, POCs, and maturity modeling.
- Familiarity with AI governance frameworks and regulatory landscapes (e.g., NIST AI RMF, EU AI Act, ISO standards) and applying them to enterprise architectures.
- Strong communication, stakeholder management, and cross-functional collaboration skills, with the ability to translate complex AI/security concepts into actionable business outcomes.
- VMCE certification (can be completed after joining).
Nice to Have
- Advanced degree preferred.
- AI security or governance-related certifications (e.g., AI/ML, privacy, or data governance) are strongly preferred.
- Experience with DRMM or data/AI trust maturity models is a plus.
Work Arrangement
Remote (Worldwide)
Additional Information
- Note: Not the primary owner for Onboarding motions nor directly responsible for Renewals
