Staff AI Engineer

Veeam Software

Staff AI Engineer designing and building production AI systems for Veeam's data intelligence engine. Leading technical decisions on data insights and threat detection globally.

Posted 6/17/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $265,600 - $680,200 per yearWebsite

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI developmentmulti-agent orchestrationprompt engineeringMCP server infrastructureRBACAI quality benchmarksadversarial prompt hardeningLLM-powered capabilitiesembeddings pipelinesdata boundary enforcement

Soft Skills

mentoringtechnical leadershiparchitecture reviewsdesign decisions