Senior Manager, Artificial Intelligence

Posted 4 Hours Ago
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Hiring Remotely in United States
Remote
Senior level
Security • Software • Cybersecurity
The Role
Lead and manage AI teams to design, train, deploy, and operate production-grade ML and generative AI systems for security detection and response. Define AI roadmap, partner with product and platform teams, uphold secure MLOps practices, mentor staff, recruit talent, and deliver scalable, observable AI integrated into production cloud environments.
Summary Generated by Built In

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 Senior Manager, Artificial Intelligence to be part of making that happen.   

   

About The Role

In this role, you advance that mission by planning and directing the AI development that turns massive volumes of security signal into faster detection and response. This work spans the full range of machine learning and AI solutions, from classical models to fine-tuned language models and agentic systems. You ensure AI initiatives, processes, and deliverables conform to the organization’s established policies, quality standards, and objectives. You also work closely with R&D Leadership, Product Management, and the Security Services (S2) organization to build scalable, production-grade AI that customers and analysts need, delivered on time.

Senior Managers carry a large scope of leadership and may have multiple managers and/or technical leads reporting to them. The right leader brings specialized subject-matter expertise in the AI domain along with a can-do attitude. They are comfortable working across functional boundaries, partnering with data scientists, platform engineers, threat researchers, and security operations analysts to push complex, ambiguous initiatives over the line.

Responsibilities

Generates and manages the day-to-day work for their team and is accountable for its outcomes. Partners with the Product team to define and deliver the 6-month AI roadmap and contributes to longer-term planning and strategy with R&D Leadership. Provides direction and clarity, removes obstacles, and leads teams that deliver high-quality, innovative AI solutions alongside architects, developers, data scientists, product managers, CSEs, and support people.

  • Set the direction for applying the right approach to each problem, from classical ML (e.g., clustering, random forests) to deep learning, fine-tuned language models, and agentic systems, in partnership with your technical peers and team members, translating complex security use cases into production-ready initiatives.

  • Partner with Architects and other leadership on the company’s technical roadmap, championing secure, observable, and scalable AI systems in cloud-native environments.

  • Oversee the design, training, deployment, and ongoing quality measurement of models and agentic experiences.

  • Drive continuous improvement in engineering and MLOps processes.  Uphold secure coding and acceptable-use standards across the full development life cycle.

  • Drive cross-functional initiatives with platform, product, and security operations teams to integrate AI into production, and see that work through to completion.

  • Mentor each team member and help them grow their technical and leadership skills, establishing career development plans and achievable goals. Build collaborative relationships across teams and stakeholders.

  • Lead recruitment for their team and be a key contributor to hiring and recruitment strategy for both full-time and co-op roles.

About You

  • Bachelor’s degree or foreign equivalent in Computer Science, Machine Learning, Data Science, or a related field, or an equivalent combination of education and experience.

  • Four years of experience in software, AI/ML, or data science roles (or a Master’s degree plus two years), including experience leading technical teams or projects.

  • Demonstrated experience leading technical teams and delivering AI/ML or Generative AI systems to production at scale.

  • Strong expertise in the production delivery of Generative AI or machine learning systems, including training, tuning, and ongoing quality measurement and evaluation (e.g., LLM-as-judge).

  • Experience with agentic frameworks (e.g., AgentCore, LangChain, LangGraph) and LLM integration.

  • Experience architecting MLOps processes and tooling for moving models from training to production, including drift monitoring and continuous learning in high-volume pipelines.

  • Familiarity with cloud-native data services (AWS preferred) and data engineering tools (e.g., Spark, Flink, Kafka, Databricks), and with infrastructure-as-code, CI/CD, and DevSecOps principles.

  • Exposure to cybersecurity concepts such as threat detection, MITRE ATT&CK, telemetry, and adversarial behavior modeling.

  • A can-do attitude, tenacity, and proven ability to work across cross-functional boundaries to drive ambiguous, high-impact initiatives to completion.

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.   

  • This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (“EAR”).  Please note that, if applicable, an offer for employment will be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations.  


Skills Required

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience)
  • Four years experience in software, AI/ML, or data science roles (Master's + two years acceptable)
  • Demonstrated experience leading technical teams and delivering AI/ML or Generative AI systems to production at scale
  • Strong expertise in training, tuning, and ongoing quality measurement of generative models and LLMs (e.g., LLM-as-judge)
  • Experience with agentic frameworks and LLM integration (AgentCore, LangChain, LangGraph)
  • Experience architecting MLOps processes and tooling, including drift monitoring and continuous learning for high-volume pipelines
  • Familiarity with cloud-native data services (AWS preferred)
  • Familiarity with data engineering tools (Spark, Flink, Kafka, Databricks) and with infrastructure-as-code, CI/CD, and DevSecOps principles
  • Exposure to cybersecurity concepts such as threat detection, MITRE ATT&CK, telemetry, and adversarial behavior modeling
  • Experience mentoring, building career development plans, and leading recruitment/hiring efforts
  • Ability to pass background checks and comply with export control authorization if applicable

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.

  • 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.
  • 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.
  • 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

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The Company
HQ: Eden Prairie, MN
810 Employees
Year Founded: 2012

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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