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 Developer to be part of making that happen.
About the Role
The Staff AI Developer builds and delivers the AI features that power Arctic Wolf Labs, working across machine learning, data science, generative AI, and agentic systems. This is a hands-on senior engineering role: you'll take significant features and components from design through production, and you'll be one of the people the team relies on to ship well.
You don't need to be a specialist in every AI discipline, but you should be comfortable working with the data science team on data science concepts, delivery mechanisms, and trade-offs across ML, generative AI, and agentic systems, enough to make sound design decisions and collaborate credibly with specialists.
Responsibilities
Design & Delivery
- Design and build production-grade AI systems and components across ML pipelines, generative AI, and agentic workflows.
- Turn ambiguous problems into working systems that unify heterogeneous data sources using rule-based, probabilistic, and ML-based approaches.
- Apply best practices for secure, observable, and scalable AI systems in cloud-native environments (AWS preferred).
- Help evaluate emerging frameworks and approaches (agentic orchestration, fine-tuning, evaluation methods) and bring recommendations to the team.
- Build and maintain ML and data pipelines for training, deploying, and monitoring fine-tuned generative AI and machine learning models.
Cross-Functional Partnership
- Work with the data science team, engineering managers, product, and security operations analysts to deliver solutions that create measurable customer value.
- Translate between disciplines, helping data scientists understand production constraints and helping partners understand what the AI solution needs.
- Collaborate with security operations, threat researchers, and product teams to ground your work in real operational workflows and quality feedback loops.
Communication
- Communicate progress, trade-offs, and technical decisions clearly, in writing and verbally, to both technical and non-technical audiences.
- Write clear technical documents: design docs, architecture decision records, and status updates the team can act on.
Hands-On Engineering & Mentorship
- Own the day-to-day engineering: write code, review PRs, debug production issues, and unblock teammates.
- Mentor mid-level and early-career engineers, and raise the bar on code quality, testing, and operational hygiene.
- Instrument AI quality, measure outcomes, and help close the feedback loop with operations teams.
About You
- 6+ years building intelligent systems, distributed platforms, or AI-enhanced applications.
- Experience designing and shipping systems that support ML, data science, generative AI, or agentic workloads, without necessarily being a deep practitioner in all of them.
- Production experience with generative AI systems (prompt engineering, evaluation, guardrails, and some exposure to fine-tuning).
- 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.
- Strong hands-on coding ability, you spend most of your time building.
- 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, 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, background, and culture. This is reflected in our multiple awards, including Top Workplace USA (2021-2024), Best Places to Work – USA (2021-2024), Great Place to Work – Canada (2021-2024), Great Place to Work – UK (2024), and Kununu Top Company – Germany (2024). Our commitment to bold growth and shaping the future of security operations is matched by our dedication to customer satisfaction, with over 7,000 customers worldwide and more than 2,000 channel partners globally. As we continue to expand globally and enhance our technology, Arctic Wolf remains the most trusted name in the industry.
Our Values
Arctic Wolf recognizes that success comes from delighting our customers, so we work together to ensure that happens every day. We believe in diversity and inclusion and truly value the unique qualities and unique perspectives all employees bring to the organization. And we appreciate that—by protecting people’s and organizations’ sensitive data and seeking to end cyber risk— we get to work in an industry that is fundamental to the greater good.
We celebrate unique perspectives by creating a platform for all voices to be heard through our Pack Unity program. We encourage all employees to join or create a new alliance. See more about our Pack Unity here.
We also believe and practice corporate responsibility, and have recently joined the Pledge 1% Movement, ensuring that we continue to give back to our community. We know that through our mission to End Cyber Risk we will continue to engage and give back to our communities.
All wolves receive compelling compensation and benefits packages, including:
- 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
Arctic Wolf is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, provincial, or local law. Arctic Wolf is committed to fostering a welcoming, accessible, respectful, and inclusive environment ensuring equal access and participation for people with disabilities. As such, we strive to make our entire employee experience as accessible as possible and provide accommodations as required for candidates and employees with disabilities and/or other specific needs where possible. Please let us know if you require any accommodations by emailing [email protected].
Security Requirements
- Conducts duties and responsibilities in accordance with AWN’s Information Security policies, standards, processes, and controls to protect the confidentiality, integrity and availability of AWN business information (in accordance with our employee handbook and corporate policies).
- Background checks are required for this position.
The base salary range for this job family is 75,000 to 246,000 CAD 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.
Skills Required
- 6+ years building intelligent systems, distributed platforms, or AI-enhanced applications
- Experience designing and shipping systems supporting machine learning, data science, generative AI, or agentic workloads
- Production experience with generative AI, including prompt engineering, evaluation, guardrails, and exposure to fine-tuning
- Experience with agentic frameworks and LLM integration patterns such as AgentCore, Amazon Bedrock, or LangGraph
- Experience partnering with data science, product, and operations teams to deliver customer-facing outcomes
- Strong written and verbal communication skills with technical and non-technical audiences
- Strong hands-on coding ability
- Experience with cloud-native data services and infrastructure-as-code or CI/CD practices
- Exposure to cybersecurity concepts including threat detection, alert triage, risk modeling, exposure management, MITRE ATT&CK, and telemetry
- Familiarity with data engineering tools such as Spark, Flink, Kafka, or Databricks
- Experience with ML quality measurement and evaluation frameworks, including LLM-as-judge and human-in-the-loop evaluation
- DevSecOps and security-first development mindset
- AWS cloud experience
Arctic Wolf Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Arctic Wolf and has not been reviewed or approved by Arctic Wolf.
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Strong & Reliable Incentives — Incentive plans in sales roles are seen as strong when targets are met, with on‑target earnings positioned as competitive. This dynamic helps explain notably higher satisfaction in sales relative to other functions.
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Equity Value & Accessibility — Equity is included for all employees across offers, broadening ownership beyond limited groups. Broad access to equity can provide meaningful upside tied to company performance.
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Leave & Time Off Breadth — Flexible paid time off and dedicated volunteer time off are core parts of the package. These options expand avenues for time away beyond standard vacation and holidays.
Arctic Wolf Insights
What We Do
The cybersecurity industry has an effectiveness problem. Every year new technologies, vendors, and solutions emerge, and yet despite this constant innovation we continue to see high profile breaches in the headlines. All organizations know they need better security, but the dizzying array of options leave resource-constrained IT and security leaders wondering how to proceed. At Arctic Wolf, our mission is to End Cyber Risk through effective security operations. To achieve this, we believe that organizations must do three key things:
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