About The Role

25 years of experience in software engineering, established in Vienna, Austria
Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B)
Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development
We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms
Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech
Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia
International team of 500+ software engineers
Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner
Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation.
Project beneficiaries ranging from large-scale enterprises to startups
Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions
Quality-first mindset, culture of innovation, and long-term client partnerships
Global and local reach – trusted by key industry players in Europe and the US

Collaborate with Global region stakeholders to identify Business needs and translate them into workable

production ready solution.

Creating data transformation infrastructure, managing data ingestion, for AI/ML related processes
Transforming models into production-ready APIs, microservices, and software applications. Monitoring model

performance, ensuring scalability, and updating systems to maintain accuracy.

Building and maintaining the necessary IT infrastructure (cloud platforms like AWS/GCP, containerization) for AI

development.

Working with data scientists, engineers, and product managers to define AI strategies and implement features.
Ensure robust documentation of AI processes, standards, and controls in line with the Bank’s data governance

policies.

Participate in Agile ceremonies and contribute to sprint planning, backlog grooming, and delivery cycles.
Stay current with emerging AI trends, including Generative AI and large language models (LLMs), and be prepared

to integrate these advanced techniques into solutions where they can drive significant business value.

Support the production of scalable and optimized AI/machine learning (ML) models
Focus on building algorithms for the extraction, transformation and loading of large volumes of real time,

unstructured data to deploy AI/ML solutions

Run experiments to test the performance of deployed models and identifies and resolves bugs that arise in the

process.

Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the

firm.

Bachelor’s or Master’s degree in Artificial Intelligence / Data Science / Computer Science / Information

Technology / Programming & System Analysis / Computer Studies / data science or a related field, with a
minimum of 3 years of professional experience as a AI Engineer

Proficient in Python, with a strong command of advanced syntax, popular libraries (e.g., Scikit-Learn), and the

ability to extend existing structures. Exhibits proficiency in Object-Oriented Programming (OOP) by implementing
S.O.L.I.D. principles and in data structures & algorithms by analyzing complexities and making efficient choices
(e.g., Numpy vs. Pandas).

Proficient in applying Generative AI by using, understanding, and tuning large language models (LLMs) for diverse

scenarios. Skilled in architecting solutions that augment core models with external logic and tools (e.g.,
Retrieval-Augmented Generation or MCP) and in developing complex, end-to-end multi-agent systems using
services like ADK, DialogFlow, or equivalent cloud services.

Demonstrates basic knowledge and practical experience in core software engineering practices, including

navigating operating systems, programming and querying languages (e.g., Java, SQL), version control (e.g., Git),
development methodologies (Agile, Waterfall), CI/CD concepts (e.g., Jenkins), testing principles, and
monitoring. Possesses a foundational understanding of design patterns, software architecture, and core cloud
technologies (e.g., GCP, AWS, or Azure).

Demonstrates basic knowledge in the theoretical and practical application of machine learning.
Capable of conducting code reviews for team members if needed
Shows proficiency in the end-to-end data lifecycle, including advanced data engineering across traditional and

cloud databases with a focus on query optimization. Highly skilled in data preprocessing, from comprehensive
cleaning and encoding to advanced feature creation. A proficient communicator, capable of translating complex
technical findings into clear, influential data stories for diverse audiences, including senior leadership. Possesses
a foundational ability to create data visualizations (e.g., using Tableau) to support insights.

Strong analytical and problem-solving skills and Excellent communication skills, both written and verbal.
Ability to work independently and collaboratively in the context of global cross-functional teams. Familiarity with

Agile methodologies and user story documentation.