Top Artificial Intelligence Jobs in Italy

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.

Provide hands-on technical leadership for AI/ML initiatives: turn ambiguous problems into production-ready solutions, design systems for predictive maintenance, anomaly detection, time-series forecasting, and large-scale multimodal ML; guide engineering trade-offs, improve quality and reliability, and coordinate across engineers, data scientists, product and domain experts.

Lead client AI transformation engagements from discovery through implementation. Develop AI strategies and roadmaps, apply product management practices to prioritize and deliver solutions, collaborate with engineering and data teams, participate in Agile delivery, mentor consultants, support business development, and ensure successful, timely delivery of AI and analytics solutions.

Intern will develop and test plant process simulation models (LNG, geothermal, heat pumps), apply ML/AI surrogate and reduced-order models for design and operational optimization, support digital development programs, perform data analysis and reporting, learn commercial simulation software, and collaborate with cross-functional teams while following HS&E standards.

Remote internship supporting social media, digital marketing, market research, brand identity, and AI-driven content strategies. Create and schedule posts across major platforms, research AI tools, build Excel databases, update social guidelines, and assist marketing campaigns under mentorship for 15–20 hours weekly (5–6 month minimum).

Remote unpaid internship supporting digital positioning, AI-powered market and competitive research, social media and Google Business optimization, content drafting, and building organized research databases to inform marketing strategy.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

Design and build Python-based AI applications, optimise performance and storage, implement CI/CD and testing, collaborate with clients and distributed teams, and support technical leads to deliver scalable, production-grade solutions.

Join Risk Advanced Technology to apply ML/AI and BI tools to risk problems, develop credit risk and quantitative models, build dashboards and automation, support digital transformation, and present analyses to clients across project phases.

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.

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

This internship involves completing internal projects, assisting engineers, learning software, and collaborating with teams on design and data analysis tasks.

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.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Work with clients and Customer Success to design, build, and maintain server-side components for an AI platform. Implement and optimize databases, RESTful APIs, security, distributed systems, and performance; troubleshoot bugs; document code and collaborate with front-end engineers.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Develop a Python-based AI/data pipeline to parse EDA outputs and PDFs, combine NLP, computer vision, LLM/LVM and graph methods to map circuit topologies, integrate historical failure data, predict failure modes, generate standardized FMEA reports, and validate the proof-of-concept with hardware engineers on a baseline board.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

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.

Build and ship LLM- and agent-powered product experiences for North, designing interfaces, evals, observability, and feedback loops to improve reliability and user outcomes. Collaborate with modelling, product, design, and customers to turn failures and feedback into measurable product and model improvements.

Build and operate the internal AI platform used by 600+ developers: secure AI coding environments, AI-assisted CI and agentic AWS workflows. Own products end-to-end, improve developer experience, ensure reliability/observability/cost-awareness, participate in on-call, and capture reusable patterns and templates for broad adoption.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Design, build, test, and deploy AI-powered applications for scientific and healthcare workflows. Develop data pipelines, integrate LLMs and RAG systems, write Python code, create evaluation benchmarks, validate AI outputs, and productionize scalable, tested solutions while mentoring teammates and guiding technical decisions.