Top Artificial Intelligence Jobs in Milan

As an AI Business Consultant, you will drive AI adoption strategies, analyse industry trends, and facilitate transformation initiatives for clients across various sectors.

Full-cycle Account Executive responsible for prospecting, presenting and closing enterprise and mid-market deals for AI-driven cyber threat defense. Work with SDRs, partners, and technical experts to demo solutions to CISOs, attend events/conferences, and manage the 360° sales process. Hybrid role based in Milan with strong onboarding and training support.

The Generative AI Engineer will define strategies for Generative AI, design and build innovative products, and mentor engineers, focusing on AI transformation for financial services clients.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, including LLM inference infrastructure, RAG, AI agents, and evaluation/observability. Design and run experiments (A/B tests), optimize systems for production performance and reliability, and iterate rapidly with product and design partners.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

Manage daily cash flow, optimize cash management and working capital, centralize payments, oversee factoring and cash pooling, manage short- and long-term financing, banking relationships, cash flow forecasting, hedging, TMS implementation, and deliver liquidity and risk reports to senior management.

Serve as the strategic finance partner driving planning, forecasting, performance management, and decision support for senior leaders. Lead core finance processes, deploy advanced analytics and AI (Power BI) to surface risks and opportunities, manage budgets and investments, and contribute to finance transformation initiatives to improve efficiency, compliance, and value creation.

Participate in a 14-day remote pilot using a qualifying Google Pixel device to interact naturally with notification-generating apps, complete daily 10-15 minute notification sorting tasks, submit daily feedback and documentation, and report technical issues. Must follow instructions and maintain confidentiality via the Upwork platform.

As an AI Senior Business Consultant, you will leverage AI technologies to drive strategic business opportunities, analyzing trends, and facilitating AI-driven transformations across multiple industries.

The Chief Data & AI Officer will lead the establishment of a company's data and AI infrastructure, ensuring reliable information capture, decision-making processes, AI system integration, and compliance with governance standards.

Design, build, and ship production-grade LLM-powered features (RAG, extraction, summarisation, agentic tooling). Build data and inference pipelines, integrate with back-ends and vector stores, ensure evaluation, monitoring, cost and performance optimisations, and champion testing and reliability alongside product and tech leads.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Remote role for ML/AI experts to assess AI-generated content, craft and answer advanced technical prompts, evaluate model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Drive AI adoption by identifying and prioritizing AI use cases, developing business cases, collaborating with data and tech teams to implement solutions, facilitating workshops, enabling stakeholder adoption, and ensuring responsible AI governance and value realization across the enterprise.

The Founding AI Full-Stack Engineer will build end-to-end features, work with LLMs, and collaborate directly with founders in a fast-paced startup environment.

Build and maintain Kong AI Gateway features (multi-LLM routing, semantic caching, MCP), implement proxying, load balancing, database support, troubleshoot bugs, optimize performance, and integrate with third-party deployment platforms.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Design, build, and scale a global voice and automation AI platform: implement STT/TTS and telephony stacks, integrate and optimize LLM APIs and RAG pipelines, create production-grade LLM orchestration and enterprise automation workflows, and support international deployment and delivery.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Build end-to-end AI features and prototypes across backend and frontend, prototype AI agent use cases, create UI/blueprints/examples to make AI workflows usable, and ship features quickly in collaboration with product and backend teams.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.