AI Engineer - Banking

About Qualysoft · 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

Responsibilities:

• • 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.
• • Work with the relevant software platforms in which the models are deployed.

Qualifications:

• • 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.