Staff AI Operations Engineer

About this role

At Arctic Wolf, you won’t just watch the cybersecurity industry evolve – you'll help lead the change. Our global Pack is made up of people who thrive on solving hard problems, moving fast, and building technology that protects organizations around the world. We’re proud to be recognized by Forbes, CNBC, Fortune, CRN, Bartner Peer Insights and IDC MarketScape – but what matters most is the work behind it: delivering real outcomes for customers through award winning innovation like our Aurora Platform. 

If you’re looking for meaningful work, smart teammates and the chance to make a real impact in a high-growth company that’s redefining security operations, Arctic Wolf is the right place for you!     Our mission is simple: End Cyber Risk. We’re looking for a Staff AI Operations Engineer to be part of making that happen.        About the Role Arctic Wolf is scaling AI across the business, and how those systems are run and operated matters as much as the models themselves. The Staff AI Operations Engineer makes frontier AI tangible and measurable: you'll own the metrics that leaders trust, manage the technical portion of our vendor partnerships our stack depends on, and build the governance that lets us move fast.

Just as important, you'll be the person who can see and provide the evidence for the end-to-end impact of our AI systems, showing how they perform on their own and together, and turning that into a narrative that communicates our story to the people who need to hear it.

This role blends business and technical judgment. You bring enough technical depth to reason about how our AI systems are built and run, and enough business sense to connect that to outcomes and to see how metrics, vendor relationships, and governance workflows fit together.

Responsibilities Provide the Evidence for End-to-End Impact • Trace the end-to-end impact of our AI systems, both standalone and working in combination, connecting model behavior, pipeline performance, and downstream customer and business outcomes into a single, coherent view.

• Turn that view into a compelling, evidence-backed narrative, pairing hard metrics with concrete examples, that communicates the value and trajectory of Arctic Wolf's AI to engineers, executives, customers, and partners.

• Build the instrumentation and reporting that makes this story repeatable and trustworthy, so impact is something we can show on demand rather than reconstruct after the fact.

Metrics and Measurement • Own the metrics and KPI framework for all AI initiatives, defining what success looks like, building dashboards that inform strategy, and ensuring quality signals feed back into continuous improvement.

• Translate AI business value into executive reporting, building the narrative that connects operational metrics to financial and strategic outcomes.

Optimization and Operational Excellence • Work with partner engineering teams on targeted optimization initiatives across AI projects to improve inference cost, latency, accuracy, and operational efficiency.

Vendor and Partnership Strategy • Manage the technical side of vendor relationships and partnerships, working with the engineering teams to drive evaluation of new capabilities, monitoring performance and compliance, and keeping our AI stack competitive.

Governance and Risk • Design and operationalize governance that allows AI to move fast responsibly, with review gates, compliance tracking, documentation standards, and escalation workflows.

Communication, Influence and Mentorship • Influence technical direction and vendor strategy without formal authority, earning adoption through rigor and credibility.

• Mentor engineers and operations teams, establishing a culture of operational excellence and continuous improvement across the AI organization.

About You • 7+ years in data, AI/ML operations, or technical program management, shipping production systems at scale.

• 5+ years in a staff or senior-level role, with a demonstrated ability to drive organizational leverage and influence across teams without direct authority.

• Proven ability to measure and articulate the end-to-end impact of technical systems, individually and in combination, and translate it into an evidence-backed story for technical and executive audiences.

• Expertise in AI metrics and evaluation, including measurement frameworks, model evaluation best practices, and dashboards that inform decisions.

• Track record managing vendor and partnership relationships, evaluating SaaS/API-based AI tools and establishing performance accountability.

• Operational and governance acumen, including designing workflows, building compliance and audit-readiness processes, and partnering with legal and security on AI risk.

• Moderate depth in Python, SQL, and data analysis, comfortable reading code, writing analytical queries, and understanding technical constraints.

• Strong systems thinking and pragmatic judgment, plus excellent communication across technical and executive audiences.

• Experience with observability tooling (Datadog, Prometheus, CloudWatch) and GRC/governance platforms (ServiceNow, OneTrust, or similar).

• Background working with AI systems such as machine learning, generative AI, and agentic workflows.

• Cost optimization and multi-cloud deployment experience.

On-Camera Policy To support a fair, transparent, and engaging interview experience, candidates interviewing remotely are expected to be on camera during all video interviews. Being on camera fosters authentic connection, improves communication, and allows for full engagement from both candidates and interviewers. We understand that technical, bandwidth, or location-related challenges may occasionally prevent video use. If this applies, candidates are required to notify us in advance so we can explore appropriate accommodations.

About Arctic Wolf At Arctic Wolf, we foster a collaborative and inclusive work environment that thrives on diversity of thought, backgr

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