• Build and ship iOS features using Swift. • Create clean mobile flows for insurance, payments, claims, renewals and financial services. • Work with product and design to simplify complex user journeys. • Integrate backend APIs and ensure mobile flows are stable, secure and reliable. • Improve app performance, crash rate, loading states, responsiveness, memory usage and battery efficiency. • Use analytics, user behaviour and production issues to improve the product. • Build AI-assisted mobile experiences only where they genuinely improve the user journey.

• This role invites you to step into a foundational engineering space where you will shape the architecture and implementation of distributed systems. • You will guide the development of our agentic workflow platform, a critical piece of infrastructure designed to bring durability and intelligent automation to our global software network. • By establishing code designs and engineering standards, your work ensures complex financial workflows run reliably without disruption. • Beyond technical delivery, you will champion an AI-forward approach to building software quickly and effectively. • You will serve as a technical guide and mentor, supporting engineers as they navigate highly ambiguous challenges and learn to leverage modern architectural tools. • Your leadership will directly influence how our global platforms evolve, setting the technical benchmark for engineering teams across the organisation.

• Leverage data to solve business problems across various business units at EcoVadis • Design, develop, deploy, and maintain scalable AI/ML systems • Design AI/ML pipelines applying best practices in MLOps / LLMOps / AgentOps • Build AI/ML engineering infrastructure and systems for batch and real-time pipelines • Run large-scale experiments and tests to ensure quality and efficiency of ML and data pipelines • Partner with scientists and engineers to make AI/ML models accessible to end-users and downstream processes

• Contribute to the design and development of AI agents integrated into live production systems • Help build and maintain benchmark datasets to evaluate agent performance, accuracy, and safety • Design and refine prompts, tool integrations, and agent workflows • Implement, test, and optimize services and tooling across the stack — backend, data, scripting, automation, and glue code • Collaborate closely with senior engineers on system design, multi-agent orchestration, and deployment • Participate in code reviews, debugging, and documentation to ensure best practices • Work in a team environment that encourages mentorship, knowledge sharing, and hands-on learning