Top Artificial Intelligence Jobs in Rome

Lead the end-to-end design of Discover, Circle’s AI-driven two-sided marketplace. Set product and design direction, solve discovery and trust challenges for creators and consumers, prototype rapidly with AI-assisted tools, collaborate with engineers through launch, and mentor designers. The role requires deep consumer marketplace experience, ownership of complex multi-user flows, shipped zero-to-one work, and the ability to operate independently in ambiguity.

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

Leads an international data science and AI team of up to eight members focused on commercial analytics and AI accelerators. Owns demand intake, prioritization, product strategy, model and data product delivery, and enterprise-scale ML/AI platform development. Partners with commercial, marketing, finance, and brand leaders to translate advanced analytics into business recommendations, revenue growth, and resource optimization. Requires executive communication, team-building, product management, and hands-on expertise in ML, LLMs, agentic workflows, cloud deployment, and pharma or healthcare analytics.

Source proprietary company data and domain expertise for frontier AI labs, manage outreach and enterprise relationships, negotiate data-sourcing agreements, and coordinate with internal data and product teams to deliver structured, training-ready datasets. Build and prioritize a pipeline of prospective data sources and enterprise partners.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

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.

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.

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.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

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.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

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.

Design scalable, secure enterprise AI architectures and end-to-end pipelines (Generative AI, ML, agentic workflows). Drive technical feasibility, prototypes/POCs, model evaluation, cost/latency optimization, governance alignment, and mentor engineering teams to deliver production-grade AI solutions.

Own design, deployment, and operation of high-performance AI GPU fabrics and datacenter networking (RoCE, RDMA, BGP/ECMP, EVPN/VXLAN). Provide staff-level architecture, cross-team technical leadership, incident escalation, automation (Python/Bash), and operational standards for global datacenter and edge deployments, including inter-datacenter transport and security.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.

Own end-to-end delivery of AI-powered automations: scope and shape client solutions, build demos and production systems (Python, FastAPI/Gradio, serverless), design prompts and data pipelines, validate outputs, and onboard clients while contributing patterns and R&D to the practice.

Provide technical support for ClickHouse and Langfuse customers across EMEA and global regions through cases, chat, Slack, community channels, and calls. Troubleshoot database, cloud infrastructure, AI application, tracing, and evaluation issues within SLA and on-call rotations. Develop documentation and educational content, assist with technical proofs of concept, mentor colleagues, escalate bugs, collaborate with Engineering and Product teams, and support customer implementations directly in codebases.

Own the architecture and production delivery of a real-time voice AI copilot. Lead streaming speech-to-text, LLM extraction, Chrome extension integration, AWS infrastructure, latency optimization, evaluation, observability, cost control, concurrency, data isolation, monitoring, and rollback. Lead the AI engineering pod, manage client stakeholders and scope, present evidence-based results, deliver production epics, and transfer knowledge to client and internal teams.

Lead end-to-end development of an AI mahjong companion, including the gameplay decision model, LLM explanation layer, valid-action integration, win detection, training pipeline, evaluation harness, and low-latency serving. Own architecture, AWS deployment, Langfuse observability, and the two-second response budget while leading a small AI pod and communicating technical decisions to the client’s CTO and engineering team.

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.

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.

The Backend Engineer will develop and maintain features for Restream web services, design backend APIs, ensure infrastructure resilience, and contribute to a collaborative team environment.