Senior Python Developer

Project description

Our customer is a top-tier investment bank with client assets of hundreds of billions globally. Reason to join us • We offer the opportunity to work in a highly professional environment where you will work with high-level financial instruments • We want you to be part of our success story and give you reasons to be proud of what you achieved as part of our fabulous team • We give you the opportunity to develop yourself and evolve in your career via our fantastic technical, business-related or soft skills training • We encourage creative-thinking in our great open-minded work environment. Frequently the relaxation rooms are the place where the most ambitions ideas are born. • We are not just professional teams, we are also friends that have fun working together • If you are an active person and you feel motivated by the creation/development of the software solutions, then this is the place to be, you will not get bored.

Responsibilities

• Collaborate with global stakeholders to understand business requirements and translate them into scalable, production-ready AI solutions.
• Design and build data transformation frameworks, manage data ingestion pipelines, and support AI/ML-driven processes.
• Deploy machine learning models as production-grade APIs, microservices, and software applications, ensuring scalability, reliability, and ongoing performance monitoring.
• Build, maintain, and optimize the technology infrastructure required for AI development, including cloud platforms (AWS, GCP, Azure) and containerized environments.
• Develop and implement algorithms for personalization, anomaly detection, and intelligent automation while ensuring compliance with regulatory and governance standards.
• Partner closely with data scientists, software engineers, product managers, and business stakeholders to define AI strategies and deliver innovative features.
• Maintain comprehensive documentation of AI processes, controls, standards, and technical solutions in accordance with the Bank's data governance framework.
• Actively participate in Agile ceremonies, including sprint planning, backlog refinement, and iterative delivery activities.
• Stay informed on emerging AI technologies, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures, identifying opportunities to create business value through their adoption.
• Develop, optimize, and support scalable AI and Machine Learning models throughout their lifecycle.
• Build robust Extract, Transform, and Load (ETL) processes for handling large volumes of real-time and unstructured data used in AI/ML solutions.
• Conduct experiments and performance testing of deployed models, identifying, troubleshooting, and resolving issues to ensure model effectiveness and reliability.
• Apply expertise in statistics, programming, and scripting languages within a collaborative, team-oriented environment.
• Work with the software platforms and deployment environments that host AI and ML solutions, ensuring operational excellence and continuous improvement.

SKILLS

Must have

• Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Information Technology, Software Engineering, Computer Studies, or a related discipline, with a minimum of 3 years of professional experience as an AI Engineer.
• Advanced proficiency in Python, including modern language features, industry-standard libraries (e.g., Scikit-Learn, NumPy, Pandas), Object-Oriented Programming (OOP), S.O.L.I.D. principles, and data structures and algorithms with a strong understanding of performance optimization.
• Proven experience in Generative AI, including the use, fine-tuning, and application of Large Language Models (LLMs). Skilled in designing AI solutions that integrate external tools and knowledge sources through approaches such as Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and multi-agent architectures leveraging platforms such as ADK, DialogFlow, or comparable cloud-native services.
• Strong understanding of software engineering fundamentals, including operating systems, programming and query languages (e.g., Java, SQL), version control systems (Git), software development methodologies (Agile, Waterfall), CI/CD practices (e.g., Jenkins), software testing, monitoring, and observability.
• Foundational knowledge of software architecture, design patterns, and cloud computing technologies, including AWS, GCP, and Azure.
• Practical experience in the theoretical and applied aspects of Machine Learning, including model development, evaluation, deployment, and maintenance.
• Ability to perform code reviews, promote development best practices, and contribute to overall code quality within the team.
• Strong expertise across the end-to-end data lifecycle, including data engineering, cloud and traditional database technologies, data modeling, query optimization, data preprocessing, feature engineering, and data transformation.
• Excellent communication and storytelling skills, with the ability to present complex technical concepts and analytical findings clearly to technical and non-technical audiences, including senior stakeholders.
• Experience creating data visualizations and dashboards using tools such as Tableau or similar platforms to support business decision-making.
• Strong analytical thinking, problem-solving capabilities, and attention to detail.
• Excellent written and verbal communication skills.
• Proven ability to work independently as well as collaboratively within global, cross-functional teams.
• Familiarity with Agile delivery methodologies, user story creation, and requirements documentation.

Nice to have

n/a