Principal AI Developer

About the Role

As a Principal AI Developer at Arctic Wolf, you will set the technical direction for your area within Arctic Wolf Labs, designing architecture that supports machine learning, data science, generative AI, and agentic feature delivery. This senior leadership role 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 must engage easily with the data science team to discuss concepts, delivery mechanisms, and trade-offs across ML, generative AI, and agentic systems—enough to make sound architectural decisions and partner credibly with specialists.

Responsibilities

• 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.
  • 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 AI solutions.
  • 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.

Requirements

• 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 modeling, 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.

Benefits

• Equity for all employees.
• Flexible time off and paid volunteer days.
• RRSP and 401k match.
• Training and career development programs.
• Comprehensive private benefits plan including medical, mental health, dental, disability, life and AD&D, and value-added services.
• Robust Employee Assistance Program (EAP) with mental health services.
• Fertility support and paid parental leave.

Pay

The base salary range for this job family is $254,000 to $382,000 USD annually. This range reflects the base pay the company reasonably expects to offer for this position, aligned to the broader job family base pay structure. Actual base pay may vary based on skills, experience, and location, including job family level. In addition to base pay, Arctic Wolf offers variable incentive compensation, new hire equity grants, and a comprehensive benefits package.

Candidates interviewing remotely are expected to be on camera during all video interviews to support a fair, transparent, and engaging interview experience. If technical, bandwidth, or location-related challenges prevent video use, candidates must notify us in advance to explore accommodations.