GenAI Platform and Operations Engineer
Crif — Italy · Posted ~1 day ago
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GenAI Platform & Operations Engineer
Job Description
We are looking for a highly motivated GenAI Platform & Operations Engineer to join our IT Operations team and support the design, implementation, and operation of cloud-based platforms enabling Generative AI solutions across the organization.
The role will be responsible for ensuring the infrastructure architecture, reliability, scalability, security, and operational excellence of cloud environments hosting AI workloads, Large Language Models (LLMs), vector databases, data platforms, and related services, working closely with development teams to understand their requirements and provide support for new and existing applications.
The ideal candidate combines strong cloud engineering expertise with an operational mindset and a passion for automation, observability, and emerging AI technologies.
The chosen candidate will join Cloud Engineering & Operations team as part of the IT Infrastructure and Operations Department.
This role entails collaborating with cross-functional teams spanning multiple countries to augment the reliability, scalability, and performance of our systems.
Key Responsibilities
Cloud Platform Management
Design, deploy, and manage cloud-native infrastructures on Azure and AWS.Support AI and GenAI platform services, ensuring availability, scalability, and performance.Implement Infrastructure as Code (IaC) solutions using Terraform.Operations & Reliability
Monitor cloud services and workloads through observability platforms.Support incidents and problem management.Ensure platform resilience, backup strategies, disaster recovery, and business continuity.Generative AI Platform Support
Support deployment and operation of GenAI services such as: Azure foundry Ai or AWS BedrockSecurity & Compliance
Ensure compliance with cybersecurity policies and regulatory requirements.Manage cloud identity and access management (EntraID, Cognito, etc..)Support vulnerability assessment and remediation activities.
Required Skill
Essential knowledge and requirements
Hands-on experience in Enterprise projects based on Generative AI technologies such as GitHub Copilot, OpenAI, Claude, and similar platforms.Bachelor's Degree in Computer Science, Engineering, Information Technology, or equivalent experience.3 / 5+ years of experience in Cloud Engineering or Cloud Operations.LLM concepts.Prompt Engineering.Kubernetes / AKS / EKS.Container security and orchestration.Cloud Networking fundamentals.CI/CD tools (Azure DevOps, GitHub Actions, Jenkins).
Nice to have
Unified platform for data, analytics, and AI like DatabricksScripting with Python, Bash, or PowerShell.Google CloudVector Databases.Observability approach and toolsHabit of working in international environments cooperating with different teams and countriesExperience supporting enterprise production environments.
Soft Skills
Strong troubleshooting and analytical mindset.Ability to work under pressure in critical production environments.Proactive attitude and tasks accountability.Strong collaboration and communication skills.Continuous learning mindset focused on emerging AI technologies.Excellent knowledge of English.
We offer a safe and inclusive environment where colleagues are encouraged to think outside the box.
CRIF is committed to creating a diverse, inclusive work environment and promoting equal opportunities throughout the employee life cycle.
We aim to attract and retain the best people and embracing gender, age, culture, religion and disability diversity
What we offer:
Type of contract: permanent
The Annual Salary for this position starts from €32,500 gross per year.
The level of classification will be determined during the selection process based on the candidate’s profile and in accordance with the National Collective Labour Agreement (CCNL) for the Tertiary, Distribution and Services sector.
The final compensation package, including any variable components (such as MBO) or additional benefits, will depend on the assessment of the candidate’s profile against the role requirements.
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