Top Artificial Intelligence Jobs in Naples

Lead storytelling and communications for Pfizer's AI-native engineering transformation: set strategy, create content and live events, manage budgets and agency relationships, build cross‑functional engagement, track success metrics, and lead a storytelling team to translate engineering work for executives and broader audiences.

Support sales by delivering technical demos, POCs, workshops and architecture guidance. Translate customer requirements into solutions, enable partners, respond to procurement requests, and coordinate with product and engineering throughout the pre-sales lifecycle.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

Lead research and deliver executive-level insights on enterprise AI strategy, producing thought leadership, advising clients and vendors, supporting sales and conferences, mentoring analysts, and driving research agenda and process improvements to accelerate clients' AI value realization.

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.

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.

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 and operate a composable, event-driven internal platform: design and ship backend services (Python/Go), frontend admin tools (TypeScript/React), integrations with SaaS and cloud APIs, BPMN/workflow orchestration, and LLM/AI tooling across the development lifecycle while owning production reliability, security, and observability.

Build and operate internal, event-driven platform services end-to-end: backend services (Python/Go) on GCP Cloud Run, TypeScript/React UIs, integrations with third-party SaaS (REST, webhooks, OAuth), BPMN workflow orchestration, and apply AI tooling across the development lifecycle while ensuring security, observability, and production reliability.

Build and operate internal, event-driven platform services and UIs across the stack. Integrate third-party SaaS via APIs/webhooks/OAuth, implement observable BPMN workflow orchestration, use AI tooling throughout the SDLC, review AI-generated code, and ensure production reliability, security, and cost control.

Build and operate internal, event-driven platform services and UI features end-to-end. Integrate third-party SaaS and cloud APIs, implement observable BPMN workflow orchestration, use AI tooling across the SDLC, ensure security and reliability in production, and contribute engineering standards and playbooks.

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

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.

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.

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.

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.

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.

Lead and build the AI foundation for an AI-native vulnerability management platform. Own AI strategy, evaluation frameworks for non-deterministic agents, fine-tuning and model-routing experiments, prototype and ship agentic features, and lead a small hands-on AI team to productionize breakthroughs in generative AI for cybersecurity.

Design, build, and operate production-grade automations that reduce manual work across Operations, Support, Finance, and Tech. Identify high-volume automation opportunities, integrate with existing systems via APIs/webhooks, apply AI/LLMs for classification/routing/summarization, and ensure reliability, observability, and iterative improvement of workflows.

Provide technical presales expertise to drive partner adoption of Red Hat AI platforms—deliver demos, RFx responses, design AI/ML pipelines, enable partners, run POCs/hackathons, mentor juniors, and feedback to engineering.

Develop and deploy production-ready Generative AI applications using LLMs and RAG. Integrate OpenAI/AWS Bedrock APIs into systems, collaborate with data engineering, tune performance, monitor deployments, and document solutions for technical and non-technical stakeholders.

Design, develop, and deploy production-grade conversational and agentic AI applications on Omilia's Cloud Platform. Work with customers to gather requirements, implement semantic models, hybrid rule/ML/GenAI dialog flows, perform dataset preparation and model testing, integrate via REST APIs, write JavaScript application logic, run TDD/unit/regression tests, analyze conversation analytics, and support customers in operation and troubleshooting.

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.