GenAI Engineer
Role Description We are looking for an AI Engineer focused on Generative AI, with the aim of transforming complex workflows and data into intelligent, automated solutions that drive our business operations. In this role, you will design, implement, and orchestrate advanced LLMs and autonomous agents to guide strategic decisions, enhance customer experiences, and solve challenging business problems, partnering closely with cross-functional teams. Main Responsibilities
• Design and Implement AI Solutions: Develop and deploy Generative AI models, autonomous agents, and conversational interfaces to address complex business challenges and automate internal workflows.
• Model Optimization: Fine-tune existing foundation models and build robust Retrieval-Augmented Generation (RAG) pipelines to ensure highly accurate, context-aware AI outputs.
• Prompt Engineering & Orchestration: Craft and optimize prompts and utilize orchestration frameworks to build multi-agent systems that handle complex, multi-step tasks.
• Business Alignment: Partner with domain experts to translate ambiguous business questions and operational bottlenecks into actionable GenAI frameworks.
• Production & LLMOps: Partner with the MLOps/DevOps teams to ensure seamless model deployment, monitor for latency, quality, and hallucinations, and adhere to CI/CD and automated testing best practices.
• Experimentation:
Design and analyze rigorous A/B and multivariate experiments to validate the efficacy and user adoption of new AI-driven features.
• Stakeholder Communication: Communicate AI concepts, system capabilities, and limitations to both technical and non-technical stakeholders.
• Integration: Collaborate with cross-functional teams, including software engineers, product managers, and data scientists, to integrate your AI agents and models into production systems.
• Continuous Learning: Stay up-to-date with the rapidly evolving advancements in the Generative AI, LLM, and NLP landscape.
Requirements:
• Agentic AI Expertise: Solid, proven track record in agentic workflows, multi-agent orchestration, and advanced prompt engineering.
• System Integration: Clear understanding of how to connect LLMs to execution layers (RPA robots, webhooks, REST APIs) to drive automated actions in enterprise systems.
• Business-Facing Mindset: Strong curiosity and willingness to immerse themselves in operational business realities to co-design effective solutions.
• Pragmatism & Speed: A test-and-learn attitude geared toward fast prototyping, evaluation, and iterative delivery.
• Language Requirement: Native or full professional proficiency in Italian, which is essential for handling Italian-language documentation, local process nuances, and direct collaboration with SMEs. This engineer will serve as the core technical engine of a dedicated, cross-functional team, with direct visibility and a measurable impact on the company's P&L.;
• Design and Implement AI Solutions: Develop and deploy Generative AI models, autonomous agents, and conversational interfaces to address complex business challenges and automate internal workflows.
• Model Optimization: Fine-tune existing foundation models and build robust Retrieval-Augmented Generation (RAG) pipelines to ensure highly accurate, context-aware AI outputs.
• Prompt Engineering & Orchestration: Craft and optimize prompts and utilize orchestration frameworks to build multi-agent systems that handle complex, multi-step tasks.
• Business Alignment: Partner with domain experts to translate ambiguous business questions and operational bottlenecks into actionable GenAI frameworks.
• Production & LLMOps: Partner with the MLOps/DevOps teams to ensure seamless model deployment, monitor for latency, quality, and hallucinations, and adhere to CI/CD and automated testing best practices.
• Experimentation:
Design and analyze rigorous A/B and multivariate experiments to validate the efficacy and user adoption of new AI-driven features.
• Stakeholder Communication: Communicate AI concepts, system capabilities, and limitations to both technical and non-technical stakeholders.
• Integration: Collaborate with cross-functional teams, including software engineers, product managers, and data scientists, to integrate your AI agents and models into production systems.
• Continuous Learning: Stay up-to-date with the rapidly evolving advancements in the Generative AI, LLM, and NLP landscape.
Requirements:
• Agentic AI Expertise: Solid, proven track record in agentic workflows, multi-agent orchestration, and advanced prompt engineering.
• System Integration: Clear understanding of how to connect LLMs to execution layers (RPA robots, webhooks, REST APIs) to drive automated actions in enterprise systems.
• Business-Facing Mindset: Strong curiosity and willingness to immerse themselves in operational business realities to co-design effective solutions.
• Pragmatism & Speed: A test-and-learn attitude geared toward fast prototyping, evaluation, and iterative delivery.
• Language Requirement: Native or full professional proficiency in Italian, which is essential for handling Italian-language documentation, local process nuances, and direct collaboration with SMEs. This engineer will serve as the core technical engine of a dedicated, cross-functional team, with direct visibility and a measurable impact on the company's P&L.;