Sales Systems Engineer

Veeam is the Data and AI Trust Company, specializing in ensuring data and AI are secure and resilient. As a Commercial Pre-Sales Systems Engineer, you will act as a trusted advisor to customers, leading pre-sales engagements and designing secure data platforms that enhance business continuity and digital transformation.

Responsibilities:

• Lead complex pre-sales engagements, including discovery, architecture design, solution positioning, and technical validation
• Act as a trusted advisor to IT practitioners, engineers, architects, and senior leaders by translating business objectives into secure, resilient, and scalable architectures
• Deliver compelling technical demonstrations and executive-level presentations that clearly articulate business value, cyber risk reduction, and operational outcomes
• Demonstrate Veeam Proof-of-Value (POV) to organizations, aligned to customer success criteria and driving positive business outcomes
• Collaborate with customers and partners to define architectural strategies supporting data resilience, ransomware recovery, compliance, and hybrid-cloud adoption
• Create tailored proposals and contribute to enterprise-scale RFP and RFx responses
• Maintain strong awareness of industry trends, emerging threats, and competitive positioning to effectively represent Veeam in enterprise discussions
• Partner closely with sales, product management, engineering, and ecosystem partners to influence solution architecture and product direction

Requirements:

• 5–7 years in pre-sales SE, solutions architecture, or similar technical leadership roles supporting mid-market and large enterprise customers
• Proven ability to lead complex technical sales cycles (discovery, solution design, POV/POC) and present to executive and technical audiences
• Broad technical depth in data resilience and enterprise infrastructure (virtualization, storage, OS, networking, cloud, and cybersecurity), including security, privacy, governance, and compliance considerations
• Foundational understanding of AI/ML/LLMs and the role trusted, resilient data plays in AI initiatives
• Self-motivated, adaptable technologist who thrives in fast-moving environments
• Experience with hyperscalers (AWS, Azure, GCP) and SaaS in modern hybrid environments (e.g. VMware, Hyper-V, containers, IAM)
• Experience with data protection/cyber resilience vendors/solutions; relevant certifications (cloud/security/architecture)
• Familiarity with observability/monitoring and operational tooling supporting resilience and recovery
• Kubernetes and cloud-native data protection/recovery
• SaaS application data resilience (e.g., Microsoft 365, Salesforce)
• API-driven automation, scripting, and infrastructure-as-code
• Cyber recovery and clean-room architectures
• Data governance, classification, and policy-driven protection models