AI Engineer: Production AI & MLOps Integrations

The Member Company; Lombardia; On-site; EUR 65,000 - 90,000; Full time

Job summary

The Member Company is seeking an AI Engineer to collaborate with technical teams and business stakeholders, translating problems into production-ready AI solutions and overseeing the lifecycle from discovery to deployment.

You will rapidly integrate AI technologies, reuse components when possible, and develop custom integrations when needed, spanning backend, frontend, data/ML, and operations in enterprise environments.

Qualifications

• Analyze business needs and translate into production-ready AI solutions.
• Design and develop AI, ML, and Generative AI apps from prototype to production.
• Integrate LLMs and AI agents with applications, APIs, data sources, and existing enterprise systems.

Responsibilities

• Analyze business needs and processes and translate them into production-ready AI solutions.
• Design and develop applications and services based on AI, Machine Learning, and Generative AI, from prototyping to production.
• Integrate LLM and AI Agents with applications, APIs, data sources, and existing enterprise systems.
• Reuse and extend components and AI building blocks, developing custom integrations or components when necessary.
• Work across the technology stack, including backend, frontend, data/ML, and operations.
• Implement DevOps and MLOps practices, managing CI/CD, containerization, and orchestration.
• Ensure the security, reliability, scalability, testing, and observability of AI applications in production environments.
• Document developed solutions and contribute to the creation of reusable patterns and components to accelerate the development of new projects.

Job description

The Member Company is seeking an AI Engineer to collaborate with technical teams and business stakeholders, translating problems into production-ready AI solutions and overseeing the lifecycle from discovery to deployment.

You will rapidly integrate AI technologies, reuse components when possible, and develop custom integrations when needed, spanning backend, frontend, data/ML, and operations in enterprise environments.