GenAI Engineer

Admiral Europe Tech

Roma

On-site

EUR 70,000 - 100,000

Full time

2 days ago
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Job summary

Admiral Europe Tech in Rome, Italy, seeks an AI Engineer focused on Generative AI to transform complex workflows into intelligent, automated solutions. You will design, implement, and orchestrate advanced LLMs and autonomous agents to guide strategic decisions and improve customer experiences.

Collaborating with software engineers, product managers, and data scientists, you will drive production readiness, MLOps practices, model monitoring, and experimentation.

Qualifications

  • Experience deploying GenAI models, LLM systems
  • Prompt engineering and orchestration
  • Collaborating with cross-functional teams

Responsibilities

  • Design and implement Generative AI solutions including LLMs, autonomous agents, and conversational interfaces.
  • Optimize models and build robust RAG pipelines for accurate outputs.
  • Craft prompts and use orchestration frameworks for multi-agent task handling.

Job description

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.
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