Staff AI Developer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Developer based in Canada. Overview Join an innovative cybersecurity environment focused on developing intelligent technologies that help organizations detect threats and strengthen their security operations. As a Staff AI Developer, you will design, build, and deploy production-ready AI solutions spanning machine learning, generative AI, and agentic systems. You will transform complex technical challenges into scalable, secure, and reliable applications that deliver measurable customer value. Working closely with data scientists, engineers, product leaders, threat researchers, and security operations specialists, you will help bring advanced AI capabilities into real-world cybersecurity workflows. This hands-on senior engineering role combines technical ownership, architectural decision-making, and cross-functional collaboration. You will also mentor fellow engineers, improve development standards, and help shape the future of AI-driven security innovation. Accountabilities - AI System Design and Development: Design, develop, and maintain production-grade AI systems across machine learning pipelines, generative AI applications, and agentic workflows, ensuring reliability, scalability, and operational effectiveness. - Data Integration and Intelligence: Translate ambiguous business and technical challenges into practical solutions that combine heterogeneous data sources using rule-based, probabilistic, and machine learning approaches. - Generative AI and Agentic Systems: Develop and optimize LLM-powered applications, evaluate emerging orchestration frameworks, explore fine-tuning approaches, and implement appropriate evaluation methods and safeguards.

- Machine Learning Infrastructure: Build and maintain data and ML pipelines for model training, deployment, monitoring, and continuous improvement within cloud-native environments, preferably using AWS. - Security and Reliability: Apply security-first engineering principles, observability, infrastructure-as-code, CI/CD, and operational best practices to ensure AI solutions remain secure, maintainable, and scalable. - Cross-Functional Collaboration: Partner with data scientists, engineering managers, product teams, threat researchers, and security operations analysts to translate operational needs into effective technical solutions and measurable customer outcomes. - Technical Communication: Communicate implementation progress, architectural decisions, risks, and trade-offs clearly to technical and non-technical stakeholders. Produce design documents, architecture decision records, and actionable status updates. - Hands-On Engineering: Take ownership of daily engineering activities, including coding, code reviews, debugging production issues, testing, and resolving technical blockers. - Mentorship and Quality Improvement: Mentor mid-level and early-career engineers while raising standards for code quality, testing, documentation, and operational practices. - AI Evaluation and Feedback: Instrument AI systems to measure quality and performance, collaborate with operational teams to establish feedback loops, and continuously improve model outputs and customer experiences. Requirements - Professional Experience: At least six years of experience building intelligent systems, distributed platforms, or AI-enhanced applications. - AI Engineering Expertise: Demonstrated experience designing and delivering production systems that support machine learning, data science, generative AI, or agentic workloads. - Generative AI: Practical experience deploying generative AI applications, including prompt engineering, model evaluation, guardrails, and some exposure to fine-tuning.