Ai Devops (Remote)

buscojobs España; La Coruña; A distancia; EUR 40.000 - 65.000; Jornada completa

Descripción de la vacante

A leading company is seeking an AI DevOps Engineer to establish workflows and infrastructure for AI model management. This role involves collaborating with teams to ensure reliable deployments, optimizing performance, and enhancing workflows in a dynamic environment. Ideal candidates will possess strong MLOps experience and expertise in CI/CD processes and cloud management.

Formación

• Strong expertise in MLOps with practical experience in CI/CD.
• Ability to collaborate and drive AI adoption.
• Experience in cloud infrastructure management.

Responsabilidades

• Design and manage scalable CI/CD pipelines for AI models.
• Automate deployment and maintenance of AI applications.
• Collaborate with cross-functional teams for seamless integrations.

Conocimientos

MLOps

CI/CD pipelines

Cloud infrastructure management

Automation

Containerization

Monitoring

Herramientas

Docker

Kubernetes

Descripción del empleo

At Leadtech, we’ve been redefining digital businesses since 2009, creating innovative online solutions that reach millions of users every month. With a diverse team of over 700 members from 23+ nationalities, we’re united by a passion for creativity and collaboration.

We specialize in delivering user-centric experiences across web and mobile platforms, where people can connect with our products like never before.

We’re proud of our global reach and committed to fostering an inclusive workplace where every individual contributes to our shared vision of bringing cutting-edge projects to life. Learn more about our journey and mission on our About Us page!

ABOUT THE ROLE

We are building an AI Lab to support the development, deployment, and lifecycle management of AI models across various business verticals. As part of this initiative, we are looking for an AI DevOps Engineer to play a key leadership role in establishing scalable workflows, infrastructure, and best practices for managing AI models in production. This person will be instrumental in shaping the operational foundation of our AI capabilities, working closely with cross-functional teams to ensure reliable, efficient, and secure deployments.

The ideal candidate will have strong expertise in MLOps, with practical experience in CI / CD pipelines, cloud infrastructure management, and automation, as well as the ability to collaborate with internal and external stakeholders to drive AI adoption.

YOUR MISSION

As a AI DevOps at Leadtech, you will :

• Design, implement, and manage scalable CI / CD pipelines for the deployment and lifecycle management of AI models and related applications.
• Conduct technical investigations of AI models, focusing on both inputs and outputs, evaluating performance, scalability, and cost-efficiency by comparing resource consumption (e.g., GPU, CPU, token usage). The engineer will also be responsible for testing models iteratively in sprints for internal demos via Scrum to ensure they meet business requirements and are production-ready.
• Automate the deployment, monitoring, and maintenance of AI-powered applications in production environments, ensuring scalability, reliability, and performance.
• Continuously improve workflows by implementing best practices in automation, orchestration, and monitoring, ensuring that AI models are efficiently integrated into production systems.
• Optimize infrastructure usage and manage costs, ensuring that cloud resources are used effectively without compromising performance or scalability.
• Implement containerization and orchestration strategies using tools such as Docker and Kubernetes to ensure scalable and fault-tolerant deployments.
• Establish and enforce security best practices for AI-centric workloads, including data encryption, access controls, and vulnerability management.
• Collaborate with cross-functional teams, including data scientists, software developers, and business teams, to ensure that AI models are integrated seamlessly into production workflows and meet business needs.
• Take ownership of AI model demonstrations, preparing and showcasing how models perform in production to Product Owners (POs) during internal sprints.
• Develop and implement logging, monitoring, and alerting frameworks to ensure system reliability and uptime for AI services.
• Participate in incident response processes, troubleshooting and resolving issues related to AI pipelines and infrastructure.
• Stay updated on industry trends, tools, and best practices in DevOps, MLOps, and AI infrastructure to drive continuous improvement.

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