AI Security & DevOps Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Security & DevOps Engineer based in Canada. This role is responsible for defining how AI systems move securely from prototype to production across a broad portfolio of client engagements. You will combine application security, DevOps, cloud infrastructure, identity, and AI-specific security expertise to establish practical production standards. The position has significant ownership over threat modeling, secure engineering practices, CI/CD controls, and agent security. You will also work directly with enterprise security teams to translate requirements into technical solutions and approval-ready evidence. With clients often operating in regulated environments and Microsoft-focused technology stacks, the role requires strong judgment around risk, scale, and production readiness. You will help shape engineering standards while remaining deeply hands-on with the systems and platforms being secured. This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Security & DevOps Engineer based in Canada. This role is responsible for defining how AI systems move securely from prototype to production across a broad portfolio of client engagements. You will combine application security, DevOps, cloud infrastructure, identity, and AI-specific security expertise to establish practical production standards. The position has significant ownership over threat modeling, secure engineering practices, CI/CD controls, and agent security. You will also work directly with enterprise security teams to translate requirements into technical solutions and approval-ready evidence. With clients often operating in regulated environments and Microsoft-focused technology stacks, the role requires strong judgment around risk, scale, and production readiness. You will help shape engineering standards while remaining deeply hands-on with the systems and platforms being secured. Accountabilities: Own and continuously improve the security standard for moving AI systems from development through production. Define and operate security gates across the delivery lifecycle, including threat modeling, architecture reviews, design reviews, and production readiness decisions. Harden applications and AI systems across authentication, identity, secrets management, data protection, egress controls, and access management. Establish controls for AI-specific risks such as prompt injection, excessive agency, tool and connector permissions, untrusted inputs, insecure agent loops, and MCP authentication. Own security-critical platform capabilities including CI/CD, automated security scanning, infrastructure-as-code, environment management, access controls, logging, and telemetry. Audit repositories and internal systems, identify vulnerabilities and weaknesses, and implement appropriate remediation. Lead security discussions with enterprise clients, engaging security teams early and translating requirements into practical technical controls. Develop threat models, security documentation, evidence packages, and other materials required to support enterprise security reviews and production approvals. Establish preferred technology and vendor patterns for authentication, secrets, telemetry, and security scanning to create consistency across engagements. Incorporate security requirements into project scoping, timelines, and production roadmaps, accounting for validation and approval processes. Raise security standards across engineering through technical reviews, pairing, mentoring, and clear written guidance. Requirements: Deep hands-on experience in application and product security, including threat modeling, vulnerability identification, remediation, and secure design. Strong DevOps and platform engineering expertise covering CI/CD, infrastructure-as-code, cloud environments, secrets management, and observability. Strong experience with Azure, with additional familiarity with AWS and/or GCP. Advanced knowledge of identity and authentication technologies, including OAuth/OIDC, SSO, SCIM, RBAC, conditional access, and Microsoft Entra. Demonstrated expertise in LLM and AI agent security, including prompt injection, excessive agency, tool and connector permissions, insecure output handling, retrieval abuse, and AI supply chain risks. Practical experience implementing secure SDLC practices, including SAST, DAST, SCA, dependency management, software supply chain controls, and automated security reviews. Strong judgment and the ability to right-size security controls according to the maturity, risk, and business impact of a system. Proven ability to work directly with enterprise security teams and communicate technical risks in terms that executives and decision-makers can understand. An AI-native mindset, with hands-on experience using modern AI tools and building or working with AI and agent-based systems. Strong ownership, initiative, and written communication skills, with the ability to create effective technical standards, security evidence, and decision-making documents. Ability to operate independently across multiple projects and priorities while collaborating effectively with engineering and client teams. Experience in regulated industries such as financial services, healthcare, or other highly scrutinized environments is a plus. Consulting, agency, or forward-deployed experience working directly with client security organizations is advantageous. Familiarity with OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, or ISO 42001 is a plus. Experience with SOC 2 or ISO 27001, AI red teaming, adversarial testing, or abuse-case analysis is desirable. Benefits: CAD $180,000–$230,000 compensation range for Canada, with actual compensation calibrated according to location, qualifications, experience, and seniority. Fully remote position for candidates based in Canada. Occasional client travel. Flexible working arrangements across North American and international teams, with most collaboration overlapping North American time zones. Medical, dental, and vision coverage. Flexible paid time off. Health FSA/HSA. Life insurance. Opportunity to work across diverse AI security, cloud, DevOps, and enterprise technology environments. Significant technical ownership and influence over security standards, production readiness, and engineering practices. Exposure to complex AI systems and emerging security challenges involving agents, tools, connectors, and AI infrastructure. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1