AI Engineer

• Design and develop Generative AI solutions, including LLM-based agents and RAG pipelines, using AWS Bedrock Agents and/or Databricks Genie
• Design, write and iterate on prompts for LLM-based agents, optimizing accuracy, reliability and cost
• Model data and build data pipelines, developing and maintaining ingestion processes on AWS and/or Databricks
• Develop and maintain data models on AWS and Databricks
• Write clean, well-documented Python code and contribute to testing and quality assurance of AI components
• Evaluate and monitor AI solutions, measuring accuracy, performance and reliability
• Build dashboards and data visualizations to present insights to business users
• Collaborate with senior engineers, consultants and client teams throughout the project lifecycle
• Stay up to date with AI developments and share new ideas with the team

Junior/Mid AI Engineer

• Design and implement end-to-end observability for AI applications and agents
• Establish common telemetry and distributed tracing across agent workflows, APIs, data services, vector stores, model endpoints, and external tools
• Build dashboards and alerts for availability, latency, errors, reliability, quality, policy violations, consumption, and service health
• Define service-level indicators, objectives, error budgets, alert thresholds, and operational readiness criteria
• Enable trace-based debugging, incident reconstruction, and controlled session replay while protecting sensitive information
• Monitor retrieval quality, data freshness, model and prompt regressions, anomalous agent loops, degraded tool performance, and unexpected runtime behavior
• Lead root-cause analysis for AI platform and runtime incidents and implement preventive controls and improvements
• Engineer reusable pipelines, templates, and controls for configuration, prompt, model, and agent-component versioning
• Implement automated deployment-readiness gates, integration tests, regression checks, security checks, and observability coverage
• Enable canary releases, feature flags, model/provider routing, fallback strategies, and rollback mechanisms
• Provide operational tooling supporting multiple models, frameworks, clouds, and agent patterns
• Maintain runbooks, reference implementations, engineering standards, and production support patterns
• Create metering, allocation, showback, budgets, thresholds, anomaly alerts, and runtime guardrails for AI consumption
• Partner with product teams to optimize model selection, routing, context size, caching, batching, retries, and tool usage
• Embed security, privacy, Responsible AI, compliance, identity, access control, secrets management, and auditability into the AI runtime
• Engineer controls for prompt injection, jailbreaks, unauthorized tool use, excessive permissions, data leakage, unsafe execution paths, and anomalous access
• Define operating processes for monitoring, support, incident, problem, change, escalation, and service recovery management
• Create production-readiness checklists, acceptance criteria, on-call runbooks, escalation paths, recovery procedures, and business-continuity requirements
• Drive automation to reduce reconstruction effort and shorten detection, diagnosis, containment, and recovery times
• Produce technical documentation and coach engineering teams on approved operational patterns
• Act as technical bridge across AI, platform, cloud, data, architecture, cybersecurity, privacy, compliance, and service management functions
• Define and monitor KPIs for reliability, observability, incident performance, cost efficiency, control coverage, audit evidence, and platform adoption
• Use operational evidence to prioritize automation, reliability improvements, cost optimization, and risk reduction

Lead AI Operations Engineer

• Valutare modelli, framework, piattaforme e strumenti di Artificial Intelligence
• Collaborare con la funzione Architetture per individuare soluzioni efficaci e sostenibili
• Definire standard tecnici, pattern architetturali, linee guida e criteri di utilizzo delle tecnologie AI
• Progettare e realizzare prototipi, proof of concept e soluzioni innovative
• Supportare i team di sviluppo e la Factory nell'integrazione di componenti AI nelle applicazioni aziendali
• Contribuire alla risoluzione di problematiche tecniche complesse e alla definizione delle strategie implementative
• Collaborare alla roadmap tecnologica e alle valutazioni make, buy o integrate
• Definire requisiti e principi per industrializzazione, riusabilità, scalabilità e manutenibilità
• Monitorare l'evoluzione del mercato AI e condividere trend, opportunità e impatti sul business
• Agire come riferimento tecnico del Team AI

AI Engineer – Technical Lead

• Develop software using Java and AI-assisted development practices
• Use Claude Code daily on real production projects
• Design, review, debug, and ensure the quality of code
• Understand, correct, and validate AI-generated code
• Collaborate long-term through a Service Agreement

AI Engineer jobs in Italy

Junior/Mid AI Engineer

Lead AI Operations Engineer

AI Engineer – Technical Lead

Senior Java Developer – AI Development