Jobs at Veeam

Own technical delivery for complex enterprise customers across deployment, integration, automation, and solution architecture. Lead hybrid cloud, on-premises, Kubernetes, container, and Linux deployments; build integrations, agents, tools, workflows, and reusable playbooks; resolve complex technical escalations; and translate data, security, privacy, and AI needs into scalable solutions. Partner with executives and technical stakeholders, mentor other engineers, and collaborate with Sales Engineering, Product, and Engineering on strategic customer initiatives.

The Executive Assistant will support the Head of Global Products and Technology, manage complex calendars, handle confidential information, and coordinate company events and travel logistics while fostering team success and inclusion initiatives.

Lead system-level and infrastructure testing in a San Jose lab. Build end-to-end test environments spanning on-premises hardware, Kubernetes, and cloud edge topologies. Develop offline validation harnesses, profile operating-system resources, execute hardware-in-the-loop automation, and maintain physical and virtual testbeds. Own automated orchestration for resetting, patching, and reconfiguring test rigs while ensuring platform stability, hardware-software integration, and deployment verification.

Lead quality strategy and automated testing for graph database architectures and high-volume reporting engines. Build test suites for graph traversals, indexing, data fidelity, aggregation accuracy, latency, and schema evolution. Design benchmarking platforms for query and memory performance, and use Kubernetes across AWS and Azure to create isolated multi-tenant database environments for regression testing.

Design and scale distributed data processing and analytics platforms supporting OLTP, OLAP, streaming, batch workloads, and AI-driven decisioning. Build reliable pipelines and integrate cloud data warehouses, lakehouses, and processing systems handling petabyte-scale data. Optimize latency, throughput, reliability, observability, and cost efficiency while collaborating with data scientists, ML engineers, and product teams.

Supports the Customer Experience team in researching customer needs and market trends, tracking services performance metrics, optimizing scalable service offerings, and assisting go-to-market activities. The intern will also explore how data and AI automation can improve service delivery efficiency and portfolio scalability. This is a 10-week summer internship for a rising senior pursuing a bachelor's degree.

Software engineering interns complete a 10–12 week primary project, developing software components, testing and debugging code, participating in Scrum ceremonies, automating routine tasks, and writing technical documentation. Projects may involve internal tools, applied research, or product features. The role is fully onsite five days per week in San Jose, California, and requires collaboration with engineering teams.

Summer 2027 Policy Engineering Intern developing Go backend code, internal tooling, testing harnesses, AI-assisted developer utilities, and evaluation frameworks. The intern will contribute to a production cloud data governance platform, collaborate with senior engineers through design and code reviews, and gain experience with distributed systems, event-driven architecture, multi-tenant SaaS, and cloud infrastructure. This is a paid, 10-week, fully onsite internship in San Jose, California.

Train and evaluate machine learning and deep learning models, diagnose training and generalization issues, conduct experiments, and develop reusable research tooling. The intern may work on LLMs, transformers, generative AI, fine-tuning, and evaluation workflows while rapidly prototyping with AI-assisted development tools. The role requires advanced quantitative coursework and graduate study in computer science, AI, machine learning, statistics, applied mathematics, data science, electrical engineering, or a related field.

Own the vision, roadmap, and customer experience for Veeam’s Knowledge Graph, reporting, dashboards, analytics, and evidence capabilities. Translate complex graph data into actionable views for security, privacy, governance, and executive users. Lead metrics, reporting quality, APIs, BI integrations, AI-agent consumption, query experiences, and enterprise-scale performance requirements. Partner with engineering, design, AI, marketing, and support while conducting enterprise customer discovery and using AI-assisted tools to accelerate product development.

Own product strategy, roadmap, execution, pricing, packaging, and go-to-market input for Veeam’s Data and AI Security portfolio. Lead and develop the product management team, align Engineering, Design, Marketing, and Sales, and represent strategy to the CEO and executive team. Guide data security posture management and AI governance priorities using customer insights, competitive analysis, data, and judgment. Integrate an acquired product line into Veeam’s broader platform.

Own product marketing strategy for Veeam Intelligent ResOps, including positioning, messaging, launches, campaigns, sales enablement, competitive strategy, analyst relations, pricing, packaging, and route-to-market support. Track pipeline, win rate, and revenue to guide business decisions. Partner with product, sales, finance, channel, alliance, and executive teams while shaping market direction and customer-driven product strategy.

Own product marketing for Veeam DataAI Privacy, including positioning, competitive differentiation, regulatory messaging, product launches, campaigns, sales enablement, analyst engagement, and public speaking. Translate privacy and AI regulations into customer and seller value, inform product and pricing decisions with market insights, and measure impact on pipeline and win rates. Partner closely with product, sales, marketing, executives, customers, and analysts.

Senior individual contributor Product Manager for cloud-native data protection. Partner with engineering, customers, and partners to define and ship Kubernetes and virtualization data-protection features, build demos and proofs of concept, measure success metrics, and strengthen ecosystem integrations. Engage sales and field teams, evangelize externally, and iterate based on feedback.

Lead hyperscaler integration strategy (AWS, Azure, GCP) for Veeam, represent partnerships, influence cross-product roadmaps, mentor product advisors, resolve complex integration escalations, advocate architectural standards, and engage industry stakeholders through presentations and advisory work.

Lead engineering for the Knowledge Graph and hyperscale data lake integrations, setting architecture, schema, and performance standards. Manage multiple teams to build enterprise-scale graph systems, data connectors, query tuning, and AI-first engineering practices. Own roadmap delivery, operational readiness, incident learning, and hiring/coaching of engineering leaders.

Own technical relationships for strategic enterprise and commercial accounts across the customer lifecycle. Develop success plans, drive activation and adoption, conduct health assessments and architecture reviews, evaluate recovery readiness, facilitate resilience simulations, identify risks and expansion opportunities, and prepare executive business reviews. Provide strategic guidance on data protection, cyber resilience, cloud adoption, and infrastructure modernization while partnering with Sales and internal teams to support renewals and measurable customer outcomes.

Leads global compensation strategy and programs. The posting provides placeholder content and does not specify actual responsibilities, qualifications, technologies, salary, travel, or clearance requirements.

Own strategic customer deployments of the Securiti AI platform across cloud, hybrid, and on-premises environments. Build integrations, automations, data pipelines, classifiers, and agent workflows; configure Kubernetes and cloud infrastructure; troubleshoot complex deployment and integration issues; translate security, privacy, governance, and AI objectives into technical solutions; and lead customer technical sessions while partnering with Sales Engineering, Product, and Engineering.

Lead cross-functional technical programs supporting mergers and acquisitions, including systems integration, application rationalization, data migration, process automation, and environment consolidation. Conduct technical discovery, requirements gathering, process mapping, gap analysis, and migration planning. Coordinate technical teams, stakeholders, resources, communications, change management, documentation, KPIs, risk mitigation, and executive reporting to ensure successful program delivery with minimal business disruption.