At Arctic Wolf, we're redefining the cybersecurity landscape. With our Pack members across the globe, we’re committed to setting new industry standards. Our accomplishments speak for themselves—from our recognition in the Forbes Cloud 100, CNBC Disruptor 50, Fortune Future 50, and Fortune Cyber 60 to winning CRN’s 2024 Product of the Year award.
We’re proud to be a Leader in the IDC MarketScape for Worldwide Managed Detection and Response Services and a Gartner Peer Insights Customers’ Choice recipient. Our Aurora Platform also received CRN’s Product of the Year in the inaugural Security Operations Platform category.
Join a company that’s not only leading—but shaping—the future of AI-driven defense, automation, and scalable backend systems.
Our mission is simple: End Cyber Risk.
We are seeking a Senior Developer – AI Threat Intel Platform to design and build next-generation systems that use agentic AI frameworks, machine learning, backend microservices, and intelligent automation to detect and mitigate emerging risks such as fraud, abuse, and anomalous behavior.
This role sits at the intersection of AI engineering, backend systems, cloud-native architectures, and autonomous decision-making , where you’ll build LangChain/LangGraph-based reasoning frameworks, scalable services, MLOps pipelines, and AI agents that enhance the organization’s proactive defense capabilities.
Candidates from advertising, financial services, or cybersecurity backgrounds are encouraged to apply.
Arctic Wolf Labs is our research and innovation division, dedicated to advancing AI, automation, and data intelligence to further our mission to end cyber risk.
The Labs Engineering team collaborates with AI researchers, data scientists, security engineers, and backend platform teams to develop autonomous detection systems, scalable microservices, MLOps pipelines, and agentic reasoning frameworks that improve defense accuracy, performance, and adaptability.
Design and develop an AI-driven Threat Intel Platform focused on fraud, risk, and anomaly detection.
Build and extend agentic frameworks using LangChain, LangGraph, or similar architectures for reasoning, orchestration, and task automation.
Design, develop, and maintain backend services and microservices using Python, Go, and cloud-native technologies.
Build secure, scalable, and high-performance systems leveraging AWS services including RDS, DynamoDB, Lambda, EKS/Kubernetes , and event-driven pipelines.
Develop and manage MLOps pipelines for scalable model training, testing, deployment, and real-time inference.
Implement end-to-end automation workflows , from data ingestion and feature engineering to autonomous inference and actioning.
Integrate LLMs and autonomous AI agents for dynamic pattern recognition, event correlation, and decision automation.
Integrate software components into robust, production-ready systems with clear documentation, testing, and maintainability.
Apply test-driven development and CI/CD practices using Git, Jenkins, Terraform, Docker, and cloud-native tooling.
Collaborate with data science, threat intelligence, and platform engineering teams to deliver intelligent, context-aware solutions.
Use advanced debugging and analytical techniques to solve complex distributed-systems and AI workflow challenges.
Mentor junior developers and contribute to team growth through knowledge sharing and technical leadership.
Participate in R&D demos, innovation initiatives, and annual hackathons to explore and showcase new ideas.
5+ years of experience in software engineering, machine learning, or backend/data systems development.
Strong focus on backend engineering with experience building large-scale, distributed, or real-time systems .
Hands-on experience with fraud/risk analytics, behavioral modeling, or anomaly detection (fintech, ad tech, cybersecurity domains preferred).
Proven experience building or integrating agentic AI frameworks (LangChain, LangGraph, Semantic Kernel, etc.).
Strong programming skills in Python (preferred) or Go, and familiarity with PyTorch, TensorFlow, or Scikit-learn.
Experience with cloud-native architectures and tools: Kubernetes, Docker, Terraform , event-driven systems.
Practical knowledge of MLOps , data pipeline design, feature stores, and real-time inference systems.
Understanding of AI automation , LLM-based orchestration, prompt engineering, and evaluation strategies.
Familiarity with cloud platforms (preferably AWS ) and distributed systems at scale.
Proven ability to work independently on large features, drive technical discussions, and deliver production-quality systems.
Strong collaboration and communication skills, with a passion for mentoring and team development.
A proactive mindset and ability to adapt existing approaches to solve new challenges.
At Arctic Wolf, we’re cultivating a collaborative and productive work environment that welcomes a diversity of backgrounds, cultures, and ideas to make our teams even stronger as we grow globally. We’ve been named one of the 50 Most Innovative Companies in the world for 2022 (Fast Company)—and the 2nd Most Innovative Security Company. We have won countless awards for our excellence in security operations and remain dedicated to providing an industry-leading customer and employee experience including:
Top Workday USA (2021–2024)
Great Place to Work (2022–2024) & Best Workplaces for Women (2024) in Canada
Best Workplaces in Tech & For Women in the UK (2023)
Top Company by Kununu in Germany (2024)
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.
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. Please let us know if you require any accommodations by emailing [email protected].
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.
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.
