26 AI Engineer jobs in Italy available for remote work from home. Apply for positions such as Full Stack Engineer (AI), Agentic AI Engineer, Senior Agentic AI Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will own end-to-end development of product features while integrating AI coding tools into your daily workflow to maximize efficiency. Additionally, you will act as a full stack seed within your team to champion AI-augmented development practices and improve cross-team collaboration.
You will design, build, and deploy production-ready AI agents and agentic workflows using frameworks like LangGraph and CrewAI. Additionally, you will optimize knowledge retrieval pipelines and implement security guardrails to ensure reliable AI solutions on AWS.
You will architect and deploy autonomous agentic workflows and multi-agent systems using cutting-edge LLM frameworks and cloud infrastructure. Additionally, you will lead technical execution, establish observability and security guardrails, and mentor engineering teams throughout the AI development lifecycle.
Participate in end-to-end development of product features across frontend and backend while integrating AI coding tools into the workflow. Contribute to the full product lifecycle from design to deployment under the guidance of senior engineers.
Own the end-to-end development of product features across frontend and backend while integrating AI coding tools to maximize efficiency. Act as a full stack seed to mentor peers and scale AI-augmented development practices across the organization.
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Evaluate and analyze LLM performance while architecting and building inference and training pipelines. You will contribute to hands-on design, model training, and deployment strategies within a technical greenfield project.
Design and build internal AI productivity tools, including coding assistants and knowledge retrieval systems, to improve engineering efficiency. Integrate AI capabilities across the software development lifecycle and experiment with emerging technologies like LLMs and AI agents.
You will build AI-powered internal tools, including coding assistants and workflow automation systems, to improve developer productivity. You will also collaborate with engineering teams to identify technical pain points and implement LLM-driven solutions.
The engineer will design, build, and deploy end-to-end agentic AI prototypes to enhance the company’s procurement platform, architecting agent-based systems primarily using AWS-native services like Amazon Bedrock AgentCore. Responsibilities also include developing production-ready Python code, integrating solutions with other teams, and supporting deployment and monitoring via CI/CD pipelines.
Lead the architectural design of complex agentic AI solutions and provide technical guidance to junior developers. Design and develop advanced agentic AI systems while ensuring adherence to ethical guidelines and regulatory standards.
You will design and develop AI agent workflows, LLM-powered application components, and backend integrations. Additionally, you will contribute to system performance optimization, evaluation metrics, and the deployment of production AI systems.
Design and implement AI agentic systems that collaborate with developers to plan tasks, write code, and deploy applications. Integrate LLMs into production workflows while managing long-context and multi-step reasoning loops.
Contribute to the design and development of AI agents integrated into production systems and build benchmark datasets to evaluate performance. Implement and optimize services across the stack while collaborating on multi-agent orchestration and system design.
Deploy, manage, and maintain large-scale AI infrastructure for customers as a domain expert. Collaborate with internal teams to provide feedback, document workarounds, and implement AI Factory projects.
Build and maintain the technical capability layer for company-wide AI productivity, focusing on agentic AI infrastructure and self-service tooling. Own the connector layer, execution environments, and AI governance to ensure safe and scalable deployment of AI workflows.
Develop deep learning-based computer vision systems for industrial automation, covering the entire pipeline from data collection to production software. Manage the machine learning lifecycle, including neural network training and deployment on industrial machines.
Develop high-performance big-data applications and cloud-native data pipelines using Scala, Databricks, and Azure services. Build and maintain full-stack applications and microservices while driving AI-assisted engineering practices.
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You will own the full development lifecycle of features from conception to deployment while building scalable, maintainable, and customer-centric systems. You will also collaborate with cross-functional teams to design innovative solutions and contribute to team growth through interviewing.
You will develop and evolve the technical backbone of the company's Conversational AI platform, including voicebot and chatbot systems. You will also design RAG architectures and optimize LLM integrations for performance, latency, and cost in production environments.
The role involves building observability, automation, and AIOps foundations while participating in root cause analysis and support insights. You will also prototype lightweight agents and optimize workflows within incident management tooling.
The main task involves designing and building applications using Python, which includes supporting component design, development, and maintenance while adhering to high technical quality standards. Responsibilities also extend to defining structured practices, designing data storage solutions, optimizing performance, and collaborating with clients and technical leaders on project execution.
Participate in research projects, interviews, and surveys to provide expert insights on workflow management tools. Share professional expertise to help researchers and organizations improve AI models and development processes.
Design physical objects using open-source CAD software to help train AI models on engineering workflows. Write and execute Python validation scripts to support the design process.
Design physical objects for 3D printing using open-source CAD software while having your workflow captured to train AI models. Write and execute Python validation scripts to support engineering design tasks.
Design physical objects using open-source CAD software while having your engineering workflow captured to train AI models. Write and execute Python validation scripts to support your design tasks across varying levels of complexity.
Design physical objects for 3D printing using open-source CAD software while having your workflow captured to train AI models. Write and execute Python validation scripts to support your engineering design tasks.
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