Responsibilities

- Develop and maintain AI and Machine Learning solutions based on business and technical requirements.
- Participate in the design, testing, and deployment of AI-enabled applications.
- Support the implementation of Generative AI, LLM, and Retrieval-Augmented Generation (RAG) capabilities.
- Participate in model evaluation, performance monitoring, and solution optimization.
- Collaborate with Data Engineers and Software Engineers to access and prepare data required for AI solutions.
- Contribute to data integration and feature engineering activities.
- Support implementation of AI services within approved enterprise platforms.
- Assist in maintaining data quality and data governance requirements.
- Participate actively in Agile ceremonies including sprint planning, stand‑ups, retrospectives, and backlog refinement.
- Deliver committed user stories and technical tasks within sprint commitments.
- Support testing, deployment, and release activities.
- Escalate risks and technical issues when appropriate.
- Follow established AI Engineering, MLOps, and DevOps standards and practices.
- Contribute to documentation, code reviews, and technical knowledge sharing.
- Support monitoring and maintenance activities for deployed AI solutions.
- Apply security, privacy, and responsible AI requirements throughout development activities.
- Work closely with Product Owners, Business Analysts, Architects, and senior engineers while supporting solution implementation activities.
- Support business requirement clarification and technical solution discussions.
- Communicate progress, blockers, and technical findings to project teams.
- Stay current with emerging AI technologies and engineering practices.
- Participate in technical communities and learning initiatives.




- Identify opportunities for process improvements and support implementation of approved enhancements.

Requirements

- Bachelor's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related disciplines.
- 2–4 years of experience in AI Engineering, Data Science, Machine Learning, Software Engineering, or related disciplines.
- Experience developing AI or analytics solutions in enterprise environments.
- Familiarity with Machine Learning, Generative AI, LLMs, and AI application development.
- Experience with Python and common AI/ML development frameworks.
- Understanding of cloud platforms such as Azure, AWS, or GCP.
- Basic understanding of Data Engineering concepts, data pipelines, and data preparation.
- Experience working in Agile delivery environments.
- Strong problem‑solving and communication skills.

Core Competencies

Demonstrates expertise in developing and maintaining AI and Machine Learning solutions with a strong focus on Generative AI, LLM, and MLOps practices. Proficient in collaborating with cross‑functional teams to ensure data quality, governance, and successful implementation of AI services.

Highest‑signal resume keywords

- AI Engineering
- Machine Learning
- Python Programming
- Agile Methodologies
- Cloud Platforms

Hard Skills

- AI Solution Development
- Machine Learning Frameworks
- Data Integration
- Feature Engineering
- Model Evaluation
- Performance Monitoring
- Solution Optimization
- Data Governance
- MLOps Practices
- DevOps Standards

Soft Skills

- Problem‑Solving
- Communication

Industry Keywords

- Generative AI
- LLM
- Retrieval-Augmented Generation
- Data Engineering
- Agile Delivery

Tools & Technologies

- Azure
- AWS
- GCP

#J-18808-Ljbffr

📌 Senior Analyst – AI Engineering (Milano)
🏢 Jobtailor
📍 Milano