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As a Business Support Specialist, you will provide exceptional support to customers via live chat, email, and phone, while advising on products and contributing feedback to improve customer experience.

As an Application Engineer II, you'll develop financial products and APIs, design scalable systems, and collaborate across teams at Mollie.

Lead a team of application engineers, drive technical roadmap and cross-domain initiatives, mentor and grow engineers, improve team velocity, and deliver scalable, fault-tolerant product solutions while balancing hands-on engineering and strategic direction.

The Senior Account Executive will drive expansion in the French market, own the sales cycle, and contribute to building a robust pipeline while collaborating with teams for customer success.

Build Mollie's Asset & Liability Management (ALM) function from scratch: design liquidity and interest rate risk frameworks (ILAAP, LCR/NSFR, IRRBB/CSRBB), develop funding and balance sheet strategy, create contingency funding plans and early-warning indicators, produce regulator-ready policies/models, and support senior leadership and ALCO with analysis and recommendations.

Lead a team of application engineers, shaping product strategy, driving technical decisions, and improving team effectiveness while mentoring talent.

Build and maintain scalable full-stack features for Customer Onboarding: design APIs, UIs and services, collaborate with product and other UI teams, solve cross-stack problems, and support CI/CD deployments.

Build and maintain high-scale backend systems and APIs for payment and data platforms. Own features end-to-end from design through production support, contribute to migrations and modernisation, and resolve complex distributed-systems issues with a product-first mindset.

Responsible for driving new business revenue from medium to large merchants in France through outbound sales and building strong client relationships.

Build, maintain, and scale Mollie’s cloud ML platform on GCP by writing production-grade Python and Terraform. Deploy and operationalize ML models, create CI/CD pipelines, manage Kubernetes model serving, implement MLOps best practices, set up observability, and support/extend open-source and generative AI tooling.