Principal AI Developer

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 Principal AI Developer to be part of making that happen.        About the Role The Principal AI Developer will set the technical direction for their area within Arctic Wolf Labs, designing architecture that supports machine learning, data science, generative AI, and agentic feature delivery. This is a senior leadership role that blends strategic vision with hands-on execution: you'll define the "how" and "where next" while rolling up your sleeves to help the team ship. 

You don't need to be a specialist in every AI discipline, but you need to be able to engage easily with the data science team to discuss data science concepts, delivery mechanisms, and trade-offs across ML, generative AI, and agentic systems - enough to make sound architectural decisions and partner credibly with specialists. 

In This Role, You'll Get To : Technical Direction & Architecture   • Own the technical vision and architecture roadmap for your team's AI capabilities - spanning ML model pipelines, generative AI features, and agentic workflows. 

• Design scalable, production-grade systems that unify heterogeneous data sources using rule-based, probabilistic, and ML-based approaches. 

• Define best practices for building secure, observable, and scalable AI systems in cloud-native environments (AWS preferred). 

• Evaluate emerging technologies and frameworks (agentic orchestration, fine-tuning approaches, evaluation methods) and advise on the right approach for Arctic Wolf's context. 

• Establish ML and data pipelines for training, deploying, and monitoring fine-tuned generative AI and machine learning models. 

Cross-Functional Partnership   • Partner closely with other product area principals and AI teams to define the best technical solution for the customer - contributing AI expertise while integrating their domain knowledge and perspectives. 

• Work with the data science team, engineering management, product, and security operations analysts to co-create solutions that deliver measurable customer value. 

• Translate between disciplines - helping data scientists understand production constraints and helping other product areas understand requirements unique to the AI solution. 

• Collaborate with security operations, threat researchers, and product teams to ground AI solutions in real operational workflows and quality feedback loops. 

• Influence product roadmaps by connecting technical capability to customer outcomes. 

Communication & Influence   • Communicate technical strategy, progress, and trade-offs clearly  - in writing, verbally, and to audiences ranging from individual contributors to executives and non-technical stakeholders. 

• Represent Arctic Wolf Labs' AI capabilities externally where appropriate (conferences, customer conversations, recruiting). 

• Write clear technical documents: architecture decision records, design docs, and status communications that a broad audience can act on. 

Hands-On Delivery & Team Leadership   • Roll up your sleeves  - unblock the team, debug production issues, review PRs, and write code when needed. Bring a "get it done" attitude that raises the bar for everyone. 

• Mentor senior engineers and foster a culture of innovation, ownership, and engineering excellence. 

• Lead by example in code quality, testing, observability, and operational hygiene. 

• Drive iterative improvement: instrument AI quality, measure outcomes, and close the feedback loop with operations teams. 

We're Looking for Someone With:   • 10+ years building intelligent systems, distributed platforms, or AI-enhanced applications. 

• 5+ years leading technical direction and mentoring senior contributors. 

• Demonstrated ability to architect systems that support ML, data science, generative AI, and agentic workloads - without necessarily being a deep practitioner in all of them. 

• Production experience with generative AI systems at scale (fine-tuning, prompt engineering, evaluation, guardrails). 

• Experience with agentic frameworks and LLM integration patterns (e.g., AgentCore, Amazon Bedrock, LangGraph, or equivalent). 

• Track record of partnering with cross-functional teams (data science, product, operations) to deliver customer-facing outcomes. 

• Strong written and verbal communication skills across technical and non-technical audiences. 

• Hands-on coding ability  - you still ship, not just direct. 

• Experience with cloud-native data services (AWS preferred) and infrastructure-as-code / CI/CD practices. 

• Exposure to cybersecurity concepts: threat detection, alert triage, risk modelling, exposure management, MITRE ATT&CK, telemetry. 

• Familiarity with data engineering tools (Spark, Flink, Kafka, Databricks). 

• Experience with ML quality measurement and evaluation frameworks (LLM-as-judge, human-in-the-loop evaluation). 

• DevSecOps and security-first development mindset. 

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, ba

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