Lead Domain Engineering Specialist

About the role

The ideal candidate will be naturally collaborative, articulate, extremely organized, have a solid technical understanding of Veeam products, and motivated by maximizing customer success and outcomes. Soft skills combined with technical skills are key in this role. You will partner with Customer Success Engineers (CSEs) and Account Executives (AEs) to drive customer outcomes across security-related products and use cases within the Veeam Data Platform (VDP).

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; advanced degree preferred.
• Relevant certifications (e.g., CompTIA Security+, CISSP, CISM, or equivalent); AI security or governance-related certifications (e.g., AI/ML, privacy, or data governance) are strongly preferred.
• 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 (experience with DRMM or data/AI trust maturity models is a plus).
• 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).

Qualifications

• 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; advanced degree preferred.
• Relevant certifications (e.g., CompTIA Security+, CISSP, CISM, or equivalent); AI security or governance-related certifications (e.g., AI/ML, privacy, or data governance) are strongly preferred.
• 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 (experience with DRMM or data/AI trust maturity models is a plus).
• 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).

Skills

• Collaboration and communication skills.
• Technical understanding of Veeam products.
• Soft skills combined with technical skills.
• Experience in cybersecurity, data security, or AI/ML-driven platforms.
• Relevant certifications (e.g., CompTIA Security+, CISSP, CISM, or equivalent).
• Deep expertise in data security and governance.
• Hands-on experience with AI security, governance, or emerging AI platforms.
• Working knowledge of AI/ML architectures and model lifecycles.
• Experience with AI/data observability, telemetry, and monitoring.
• 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.
• Strong communication, stakeholder management, and cross-functional collaboration skills.
• VMCE certification (can be completed after joining).

Benefits

• Unlimited paid time off, 12 paid holidays including 4 global Veeam Days for self-care and 24 paid volunteer hours annually through Veeam Cares.
• Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents.
• Medical, dental, and vision coverage starting on your first day.
• Mental health support, therapy sessions, and digital wellness tools via our Employee Assistance Program.
• 401(k) retirement plan with company matching contributions.
• Fertility, adoption, and surrogacy support through Maven, plus paid volunteer time.
• AirVet: 24/7 virtual veterinary care at no cost.
• Legal services, identity protection, and supplemental health insurance options.
• Tax-advantaged spending accounts for healthcare, dependent care, and commuting.
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O'Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning.

Pay

Compensation Transparency: Veeam is committed to pay transparency and equitable compensation. For this role, the compensation range below reflects the expected total target compensation (TTC), inclusive of base pay and a competitive performance-based bonus. For roles with a commission plan, the compensation range represents On Target Earnings (OTE), which includes base salary plus variable commission. When determining compensation, Veeam takes into consideration factors such as experience, education, skills, and geographic zone. Offers are typically made below the midpoint of the range.

Schedule

Veeam offers a flexible schedule to accommodate the needs of its employees.