Your New Company
Kirey is one of the leading European groups specializing in technology consulting and system integration, with a distinctive positioning in data-driven innovation.
Through a comprehensive portfolio of solutions—including Data & AI, Cloud, Software Development, Cybersecurity, Infrastructure & Automation, and Monitoring—Kirey transforms data complexity into intuitive and accessible solutions, enabling its clients to achieve their business objectives.
Headquartered in Italy, with a solid international presence and nearly 1,500 employees, Kirey has delivered more than 10,000 projects for leading clients across industries such as Insurance, Banking, Manufacturing, Retail, Public Administration, and Services & Energy.
At the core of all this are people, who at Kirey are empowered to fully express their talent and actively contribute to the company’s value chain. This is made possible through continuous investment in improvement processes and training, the promotion of innovative ideas and creativity through skills development, and a strong commitment—expressed through dedicated initiatives—to inclusion and diversity.
YOUR ROLE
We are looking for a GEN AI Engineer role
WHO WE ARE LOOKING FOR
The ideal candidate has 1-5 years five years of experience in design, build, and industrialize Generative AI and agentic solutions — from prototyping to production — using modern LLM, RAG, and cloud-native technologies.
Responsibilities
Design, develop, and industrialize GenAI applications, from prototyping to production deployment
Develop agentic workflows and LLM-based solutions, including RAG, function calling, and service orchestration
Design, train, and fine-tune machine learning models to complement GenAI solutions where traditional ML approaches are more suitable
Select and evaluate the most appropriate approach (traditional ML, fine-tuned models, or LLM-based solutions) based on use case requirements and constraints
Deploy and operate GenAI and ML solutions on cloud infrastructure (preferred AWS ), leveraging Databricks (nice to have) for data and AI pipelines where relevant
Use AI-assisted development tools (GitHub Copilot, Claude, and similar solutions) to accelerate coding,
testing, refactoring, and code review
Implement MLOps/LLMOps practices, including model versioning, automated retraining, and performance monitoring in production
Collaborate with cross-functional teams (Product, Cloud, Data, Security, and Business) to bring innovative solutions into production
Define standards, frameworks, and best practices for adopting Generative AI in enterprise contexts
Requirements
1 to 5 years of hands-on experience in the role
Familiarity with the principles of developing LLM-based applications, prompt engineering, RAG, and API integration
Experience at least one GenAI framework such as LangGraph, LangChain, LlamaIndex, or Semantic Kernel
Strong proficiency in one or more modern programming languages (Python, TypeScript, ..)
Experience using Generative AI tools to support application development
Basic understanding of machine learning concepts and model development lifecycle (training, evaluation, deployment)
Knowledge of design patterns, development principles, and modern application architecture
Knowledge of key Software Delivery practices (CI/CD, code review, testing, and quality engineering)
Working knowledge of AWS cloud services (e.g. SageMaker, Bedrock, S3, Lambda, EC2)
Experience building agentic solutions using frameworks such as Strands Agents, with familiarity with agent interoperability protocols : MCP, A2A. (Mosaic AI Agent Framework nice to have)
Ability to translate business and process requirements into concrete technological solutions
Fluent English
Nice to have
Experience developing agentic systems and multi-agent workflows
Knowledge of Azure OpenAI, OpenAI API, or other enterprise AI platforms
Knowledge of Databricks for data engineering, ML pipelines, and GenAI workloads
Familiarity with vector databases and semantic search solutions
Experience with DevOps, Docker, Kubernetes, and cloud-native architecture
Knowledge of LLMOps, observability, evaluation frameworks, and AI application governance
Experience in industry-specific contexts such as manufacturing, engineering, pharma, airports/transportation, fashion, or gaming/betting
Professional certifications in AWS, Azure, or Databricks, particularly in AI, Generative AI, Data Engineering, or Solutions Architecture paths
Professional certifications in AWS, Azure, or Databricks, particularly in AI, Generative AI, Data Engineering, or Solutions Architecture path
WHAT WE OFFER
The proposed salary includes a gross annual salary (RAL) ranging between €30,000 and €40,000 , depending on skills and experience.
ADDITIONAL BENEFITS
Challenging and innovative projects
Dynamic and merit-based environment
Agile team collaboration
Professional growth plan
Training courses and certifications
Welfare & Benefits system
Lavoro da remoto or full remote options (genuinely available❗) with flexible hours
JOIN US
Location: Roma or Florence (Hybrid)
We adopt a hybrid working strategy designed to leverage the opportunities offered by remote work for both employees and the company. Our approach reflects the belief that an employee’s impact, contribution, and results matter more than their physical location.
Kirey promotes diversity in the workplace. All applications for open positions are welcome and will be assessed based on merit.
DATA PROTECTION NOTICE
Your personal data will be processed for recruitment purposes (execution of pre-contractual measures) by Kirey S.r.l., headquartered at Viale Francesco Restelli 5, 20124 Milan, Italy, represented by its legal representative, and/or by other companies under its control. These entities may be contacted at .
You may exercise your rights under Articles 15–22 of the GDPR, including lodging a complaint with the Data Protection Authority. Data will be retained for a maximum of 24 months (unless interrupted or suspended) and will not be disclosed.
The full privacy notice is available here: or upon request at
📌 GEN AI ENGINEER (Roma)
🏢 Kirey
📍 Roma