AI Governance & Platform Engineer (ID: 3863)
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AI Governance & Platform Engineer (ID: 3863)
Location
Amsterdam, Netherlands
Experience
Mid
Posted
Jul 14, 2026
Apply by
August 13, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
As an AI Governance & Platform Engineer, you will:
- Design, implement, and maintain AI governance frameworks aligned with enterprise risk policies and responsible AI principles
- Define governance processes across the complete AI lifecycle including data management, model development, deployment, monitoring, compliance, and reporting
- Establish and enforce AI governance controls to ensure AI solutions are secure, compliant, auditable, and aligned with business requirements
- Govern Azure AI platforms including Azure OpenAI, Azure Machine Learning, and Azure AI services
- Implement governance using Azure Policy, RBAC, security controls, and compliance frameworks
- Maintain visibility, inventory, and lifecycle management of AI assets across enterprise environments
- Build and maintain platform engineering solutions, tooling, and automation frameworks supporting AI/ML pipelines
- Develop reusable tools, dashboards, and automation solutions to monitor AI governance compliance and risk exposure
- Integrate governance and security controls into CI/CD pipelines and DevSecOps workflows
- Implement security and vulnerability management practices for AI models, data pipelines, APIs, and AI services
- Perform continuous vulnerability scanning, risk assessment, remediation tracking, and security improvement activities
- Address AI-specific security risks including data leakage, model extraction, and prompt injection vulnerabilities
- Collaborate with security teams, data teams, cloud engineers, compliance teams, and business stakeholders to deliver secure AI platforms
What You Bring to the Table:
- 5+ years of experience in cloud engineering, AI platform engineering, DevOps, security engineering, or related technology roles
- Strong experience with Microsoft Azure cloud services, AI platforms, and cloud governance practices
- Hands-on experience with Azure OpenAI, Azure Machine Learning, and Azure AI services
- Strong understanding of AI governance principles, responsible AI practices, risk management, and compliance frameworks
- Experience implementing governance controls using Azure Policy, RBAC, and security management capabilities
- Experience building and maintaining DevOps/MLOps pipelines and automation frameworks
- Strong knowledge of CI/CD practices, DevSecOps principles, and security automation
- Experience with vulnerability management, security scanning, risk assessment, and remediation processes
- Understanding of AI security risks and best practices for securing models, data, APIs, and AI workloads
- Experience with Infrastructure as Code, automation tooling, and policy-as-code approaches
- Strong analytical and problem-solving skills with the ability to translate governance requirements into technical solutions
- Strong communication skills with the ability to collaborate with technical and non-technical stakeholders
You Should Possess the Ability To:
- Design and implement scalable AI governance and platform engineering solutions
- Translate AI risk, compliance, and security requirements into automated technical controls
- Build secure and compliant AI platforms aligned with enterprise standards
- Improve visibility, monitoring, and governance maturity across AI environments
- Collaborate effectively with cloud, security, data, and business teams
- Identify security risks and implement sustainable mitigation strategies
- Drive automation and continuous improvement across AI delivery processes
- Work independently while contributing effectively within a collaborative engineering environment
What We Bring to the Table:
- Opportunity to work on enterprise AI transformation, governance, and cloud security initiatives
- Exposure to Azure AI platforms, DevSecOps, MLOps, and responsible AI practices
- Opportunity to build secure, scalable, and compliant AI solutions
- Collaboration with cloud, security, data, and technology teams
- Growth opportunities through challenging AI governance and platform engineering projects
Let’s Connect
Want to discuss this opportunity in more detail? Feel free to reach out.
Recruiter: Asha Krishnan
Phone: +31 20 369 0609 ; Extn :146
Email: asha.k@stafide.nl
LinkedIn: https://www.linkedin.com/in/asha-krishnan
Key Responsibilities
- Design and maintain AI governance frameworks aligned with enterprise risk policies
- Define governance processes across the complete AI lifecycle including data management and model deployment
- Establish and enforce AI governance controls to ensure security and compliance
- Govern Azure AI platforms including Azure OpenAI, Azure Machine Learning, and Azure AI services
- Implement governance using Azure Policy, RBAC, and security controls
- Maintain visibility and lifecycle management of AI assets across enterprise environments
- Build platform engineering solutions and automation frameworks for AI/ML pipelines
- Develop tools and dashboards to monitor AI governance compliance and risk exposure
- Integrate governance controls into CI/CD pipelines and DevSecOps workflows
- Implement security and vulnerability management practices for AI models and data pipelines
- Perform continuous vulnerability scanning and risk assessment
- Address AI-specific security risks such as data leakage and prompt injection
- Collaborate with security, data, cloud, and compliance teams
Skills Required
Microsoft AzureAzure OpenAIAzure Machine LearningAzure AI servicesAzure PolicyRBACDevOpsMLOpsCI/CDDevSecOpsInfrastructure as CodePolicy-as-codeVulnerability managementSecurity scanningRisk assessmentAnalytical skillsProblem-solvingCommunicationCollaborationAbility to translate requirements into technical solutions
Benefits
- Opportunity to work on enterprise AI transformation
- Exposure to Azure AI platforms, DevSecOps, MLOps, and responsible AI practices
- Collaboration with cloud, security, data, and technology teams
- Growth opportunities through challenging AI governance and platform engineering projects
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