Senior AI Engineer
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Location
In office (Bucharest)
Seniority
Senior · 5+ years exp
Confirmed on the employer's own hiring board on Nov 13, 2026. First seen by Alion on Nov 11, 2026.
Overview
Company
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UniCredit is a pan-European commercial banking group headquartered in Milan, Italy, serving retail, private, corporate and institutional clients, and unicredit.it is the website of its Italian retail bank. The group, listed on the Milan stock exchange, operates major banks in Germany through HypoVereinsbank, in Austria through Bank Austria and across Central and Eastern Europe, including Romania, Hungary, Serbia and Bulgaria. Its careers board lists client advisers, wealth advisers, branch service staff, interns and working students in corporate banking, cash management and trade finance, mainly in Munich, Vienna, Milan and Bucharest.
- University degree in computer science, physics, mathematics or engineering.
- 5+ years of practical relevant experience in software design and implementation, ideally related to AI systems
- In-depth knowledge of Software Engineering best practices, design and architectural patterns.
- Experience in object-oriented software development in Python, knowledge of APIs design and implementation - additional languages are a plus.
- Practical knowledge of Kubernetes and Docker.
- Hands-on experience with AI systems in production, embedded into enterprise ecosystems.
- Experience with Agentic AI system design, development and maintenance in an enterprise setting with production grade infrastructure.
- Proven experience in application development, leveraging cloud infrastructure, including cloud services usage and integration. (Google preferred, Azure nice to have)
- Eager to learn and stay up to date to AI trends, technologies and framework
- Excellent collaboration skills, with the ability to work effectively in an agile environment.
- For more senior roles, experience in leading the delivery of technical teams bridging gaps between methodological and engineering effort guaranteeing smooth transition between prototyping and production grade system.
- Practical experience in using ML and/or AI frameworks (e.g. KubeFlow, Langchain, Haystack, ...)
- Experience and Machine Learning Engineer - MLOps lifecycle for traditional AI systems.
- Experience with Open Source LLMs in production, LLM fine tuning and deployment.
- Experience in testing strategy (unit test, integration test, scalability test) with a focus on AI systems and LLM scalability.
- Experience in designing and developing microservices architecture.
- Knowledge of DevOps best practices, with proven experience of deployments on Kubernetes.
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