Top Artificial Intelligence Jobs in Italy

Lead development and ownership of sustainability-focused data and AI products: design data models, automated ingestion pipelines, governance, analytics and consumption layers (APIs, dashboards), collaborate across engineering, data science and business teams to meet regulatory and reporting frameworks.

Own and scale AI enablement: build core orchestration, LLMOps/MLOps platforms and governance, integrate generative AI into product, optimize cost/latency, run PoC-to-production delivery, upskill teams, standardize tooling and vendor strategy, and track adoption/ROI metrics.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.

Design and deliver Salesforce solutions focused on AI and automation. Translate business needs into architectures and integrations, develop AI use cases (Agentforce, Einstein, Copilot), support project teams, mentor juniors, and manage client stakeholders.

Design, build, evaluate, and deploy LLM-driven features and AI systems. Collaborate with engineering and product teams to implement RAG, monitoring, CI/CD, and scalable cloud ML deployments while continuously improving model performance.

As an AI Creative Producer, you'll develop and scale AI-generated content across various platforms, collaborate with teams, and enhance production workflows.

The AI Infrastructure Engineer will build and manage scalable model serving infrastructure for AI/ML applications, ensuring high efficiency and reliability in production.

Lead AI search strategy to secure brand authority in LLM-driven results. Design and run tests to measure LLM visibility, build analytical frameworks, integrate data sources, collaborate with Product/Engineering to optimize ingestion, and drive PR/community strategies to shape AI perception.

Review, evaluate, and annotate AI-generated text, images, audio, and video for quality, consistency, and guideline compliance. Identify edge cases, perform calibration activities, provide feedback to improve annotation workflows, and contribute to high-quality multilingual datasets for training generative AI models.

As an AI Engineer at Lexroom, you will build full-stack features using Next.js and Python, optimize APIs and databases, and collaborate with teams to enhance legal software products.

The Business Development Rep will qualify clients and manage outreach in AI Cloud sales, engaging technical audiences and developing partnerships.

The role involves evaluating AI-generated outputs, analyzing multimedia content, providing feedback, and ensuring culturally relevant content based on local insights. Attention to detail and analytical skills are essential.

Act as site-level AI ambassador: identify and evaluate AI/ML opportunities, translate business problems into measurable POCs, coach teams on AMP 2.0, run feasibility tests with central AI, and scale successful POCs to production while driving business impact.

Senior individual contributor who architects, prototypes, and productionizes agentic AI and ML forecasting solutions for Finance. Designs multi-agent systems, ML models for forecasting and anomaly detection, establishes governance/responsible AI practices, and partners with FP&A, Engineering, IT, and Security to deliver measurable automation and forecasting impact.

Support the design and implementation of AI solutions, collaborating with teams, and gaining hands-on experience in machine learning and NLP.

This program involves developing and deploying AI models, collaborating with teams, and working on high-impact products in a structured training program.

Seeking a Senior Full-Stack Engineer to develop AI-driven web and mobile applications, focusing on scalable architectures and API integrations. Collaborate with product teams to translate features into technical solutions.

Build and own end-to-end features for Chainguard's AI-enabled CI/CD and supply-chain security products. Design, implement, and iterate on integrations like hardened GitHub Actions, container tooling, and agentic AI features. Drive architectural decisions, collaborate with Product and front-end teams, and ship secure, production-ready developer tools.

Lead design and implementation of CI/CD and AI-related product features, owning end-to-end delivery. Build and secure CI/CD systems, work with containers, registries, and Kubernetes, extend agentic AI into customer experiences, guide architecture, and collaborate closely with Product and front-end teams.

Build and ship secure, production-ready CI/CD and AI-integrated features end-to-end. Design, implement, and iterate on products (e.g., hardened GitHub Actions, agent features), work closely with Product and front-end teams, make architectural decisions, and extend Chainguard's agentic AI capabilities into customer-facing experiences.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide clear, opinionated feedback, distinguish response quality levels, and help define best practices for AI-assisted developer workflows.

Lead end-to-end technical projects for a Voice AI CX platform: scope, plan, manage releases, align product to customer requirements, track metrics, ensure quality, and communicate status to clients and engineering.

Own SEO strategy and KPI progress for client accounts, build AI-supported workflows and automations, create repeatable SEO processes, lead client communications and reviews, and drive measurable visibility and business outcomes by combining AI tools and specialist expertise.

Senior technical lead embedding with customer teams to design, architect, and deliver production-grade AI/ML solutions. Drive model optimization, high-performance training (TPUs), efficient serving (vLLM), MLOps, agentic systems, GDPR-compliant private AI, ROI and cost optimization, pre-sales technical support, mentoring, and external thought leadership.

Build and maintain the marketing automation backbone and AI agent integrations. Implement event tracking, data pipelines, CRM customizations, and cross-channel workflows. Prototype agent infrastructure, connect APIs/webhooks, automate go-to-market tasks, and produce analytics and attribution to support growth and experimentation.