Company Description
Varrlyn is a consulting firm which was founded in 2010 and is based in The Netherlands. We help financial institutions with system implementations and provide some serious application support, concentrating on the way they process transactions and deploy reporting applications.
Varrlyn has a proven track record: we have worked for financial institutions in Amsterdam, Brussels, London, Paris, New York, Frankfurt, and Sydney. We help improve cost efficiency, simplify application architecture, optimize time to market, enhance straight-through processing, and ensure compliance with financial regulations. In other words: You do the deal, we’ll do the project.
Job Description
Build the future of AI-driven banking
Our client's Agentic AI Centre of Excellence is building the next generation of AI-powered products and engineering capabilities. We are looking for engineers who don't just implement AI solutions—they shape how they are designed, validated, and scaled across one of Europe's largest banks.
You are someone who naturally experiments, challenges assumptions, and turns ideas into working software. You don't wait for perfect requirements. You reduce uncertainty by building, testing, measuring and iterating.
What you'll do
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Design and build production-grade Agentic AI applications.
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Architect AI systems using modern orchestration frameworks such as LangGraph or similar.
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Design reusable AI platform capabilities that can be adopted by multiple engineering teams.
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Build scalable cloud-native services using modern software engineering principles.
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Evaluate AI systems using quantitative metrics and continuously improve their performance.
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Translate prototypes into secure, reliable enterprise solutions.
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Challenge existing ways of working and help shape engineering best practices across the organization.
Qualifications
Must-have requirements:
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5+ years of hands-on software engineering experience with a strong foundation in backend or full-stack development.
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Proven experience building production-grade Agentic AI or LLM applications, not just prototypes.
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Deep understanding of AI architecture, including orchestration, design trade-offs, and scalable AI system design.
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Hands-on experience with LangGraph, LangChain or similar agent frameworks, combined with Python.
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Strong cloud and platform engineering skills, preferably Azure, Kubernetes, Docker and CI/CD.
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Experience building scalable microservices and distributed systems in an enterprise environment.
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Able to measure and optimize AI performance, using metrics, evaluation frameworks and continuous improvement.
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Strong bias toward action, with experience rapidly prototyping, validating ideas and driving change in ambiguous environments.
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Demonstrated ownership and measurable business impact, with clear examples of technical decisions that improved products or processes.
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Excellent communication skills, able to explain technical decisions, challenge existing approaches and inspire confidence through enthusiasm and curiosity.
Additional Information
Acquisition in response to this vacancy is not appreciated.
