Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.
The VDC Intelligence team is Veeam’s AI and data intelligence engine, operating across the full platform to deliver threat detection, agentic infrastructure, and AI Trust capabilities at enterprise scale. As a Staff AI Engineer, you will design, build, and own production AI systems that help Veeam’s customers extract meaningful insights from their enterprise data, leading technical decisions on agentic workflows, threat detection, LLM-powered assistants, and the MCP infrastructure that ties it all together. This is a software engineering role at its core: you will own capabilities end to end, from API and service design through AI integration, cloud infrastructure, and production operations. You will also mentor peers, drive architectural decisions, and partner closely with product and platform teams to deliver customer-facing impact.
What You’ll Do- Lead agentic AI development, including multi-agent orchestration patterns, agent-to-agent protocols, and reliable tool use at production scale
- Own prompt engineering and evaluation workflows including structured outputs, hallucination reduction, and behavioral consistency
- Build and own MCP server infrastructure that exposes backup data to AI agents via the Model Context Protocol, enforcing tenant-aware RBAC, query constraints, and safe tool boundaries
- Define AI quality benchmarks for retrieval relevance, summarization accuracy, and agent reliability, and drive systematic improvements through eval-driven iteration
- Champion security and safety in AI systems, including adversarial prompt hardening, jailbreak resistance, data boundary enforcement, and OWASP LLM Top 10 awareness
- Tune AI workflows for performance, cost, latency, and observability across billions of documents in global regions
- Mentor engineers on the team, raise the technical bar, and contribute to architecture reviews and design decisions
Azure OpenAI Service, Kubernetes, Cosmos DB, Blob Storage, Event Bus, Model Context Protocol (MCP), OAuth 2.0, OIDC, Azure AD / Entra ID
What You’ll Bring- Proven experience integrating AI/ML services and APIs into production backend systems, including APIs, async pipelines, and cloud infrastructure, treating models and inference endpoints as components in a larger service architecture
- Hands-on experience shipping LLM-powered capabilities end to end, such as embeddings pipelines, RAG, summarization, or LLM-powered assistants, with a strong understanding of failure modes
- Experience designing and operating multi-step agentic workflows with real tool use, including strategies for reliability, observability, and recovery
- Working knowledge of Model Context Protocol (MCP), including building MCP servers, designing tool exposure contracts, or integrating MCP into agent workflows
- Experience with prompt engineering and evaluation including structured outputs, hallucination reduction, evals frameworks, and LLM observability tooling
- Experience building multi-tenant systems with data boundary enforcement, tenant-aware access controls, and LLM safety guardrails
- Familiarity with authentication and authorization patterns including OAuth 2.0, OIDC, JWT, and API key management in cloud backend systems
- Experience integrating with enterprise identity providers such as Azure AD / Entra ID or Okta
- Familiarity with AI governance concepts including data access policies, audit trails, or agent guardrail frameworks
- Background working with heterogeneous, multilingual, or large-scale enterprise data environments
- Experience with adversarial prompt hardening and OWASP LLM Top 10 security patterns
What you'll get
- Unlimited paid time off, 12 paid holidays including 4 global VeeaMe 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
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.
In addition to compensation, Veeam provides a comprehensive benefits package, including health coverage, retirement plans, and unlimited time off.
Veeam Software is an equal opportunity employer and does not tolerate discrimination in any form on the basis of race, color, religion, gender, age, national origin, citizenship, disability, veteran status or any other classification protected by federal, state or local law. All your information will be kept confidential.
Personal data collected during the recruitment process will be processed in accordance with our Recruiting Privacy Notice, which explains how your information is collected, used, and handled in connection with hiring activities. By applying for this position, you consent to this processing.
By submitting your application, you confirm that the information provided, including any supporting documents, is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification may result in disqualification from consideration or, if discovered after employment begins, termination of employment.
Skills Required
- Proven experience integrating AI/ML services and APIs into production backend systems, including APIs, async pipelines, and cloud infrastructure
- Hands-on experience shipping LLM-powered capabilities end to end (embeddings pipelines, RAG, summarization, LLM assistants) with understanding of failure modes
- Experience designing and operating multi-step agentic workflows with real tool use, including reliability, observability, and recovery strategies
- Working knowledge of Model Context Protocol (MCP), including building MCP servers, designing tool exposure contracts, or integrating MCP into agent workflows
- Experience with prompt engineering and evaluation, including structured outputs, hallucination reduction, eval frameworks, and LLM observability tooling
- Experience building multi-tenant systems with data boundary enforcement, tenant-aware access controls, and LLM safety guardrails
- Familiarity with authentication and authorization patterns including OAuth 2.0, OIDC, JWT, and API key management in cloud backend systems
- Experience integrating with enterprise identity providers such as Azure AD / Entra ID or Okta
- Familiarity with AI governance concepts including data access policies, audit trails, or agent guardrail frameworks
- Background working with heterogeneous, multilingual, or large-scale enterprise data environments
- Experience with adversarial prompt hardening and OWASP LLM Top 10 security patterns
Veeam Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Veeam and has not been reviewed or approved by Veeam.
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Healthcare Strength — Healthcare coverage is comprehensive with options that include employee-only no-cost tiers, plus mental-health support through an assistance program. Feedback suggests these offerings compare well in tech.
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Leave & Time Off Breadth — Time off includes unlimited PTO in the U.S., paid company holidays, quarterly company-wide recharge days, and paid volunteer time. Feedback suggests team norms influence how fully this flexibility is utilized.
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Strong & Reliable Incentives — Sales and pre-sales roles feature meaningful on-target earnings with competitive base and variable structures. Feedback suggests these plans provide strong upside for high performers.
Veeam Insights
What We Do
Veeam provides a single platform for modernizing backup, accelerating hybrid cloud and securing data. Veeam has 400,000+ customers worldwide, including 82% of the Fortune 500 and 69% of the Global 2,000. Veeam’s 100% channel ecosystem includes global partners, as well as HPE, NetApp, Cisco and Lenovo as exclusive resellers, and boasts more than 35K transacting partners worldwide.
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