EcoVadis

AI Engineer

• Leverage data to solve business problems of various business units at EcoVadis
• Design, develop, deploy and maintain scalable AI/ML systems
• Design AI/ML pipelines by applying the best practices in MLOps / LLMOps / AgentOps
• Build AI/ML engineering infrastructure and systems to orchestrate 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
• Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Foundry) and Databricks to deliver end-to-end solutions

Senior AI/ML Engineer

Data Engineer

• Building target architectures and long-term strategic roadmaps alongside Solutions, Engineering, Data and IT teams.
• Become the owner of the Data Strategy on the architecture side, translating complex business needs into pragmatic, future-proof architectures.
• Define and govern Enterprise Data Models and Domains, expanding beyond traditional analytics to AI/ML workloads.
• Lead the architecture side of the Data Strategy, specifically designing for "AI-readiness" by integrating Feature Stores, Vector Databases and other technologies into our long-term roadmap.
• Explore and validate new solutions in the data platform space based on business requirements or research.
• Perform technical Proof of Concepts, document them, and assist teams in industrializing them.
• Monitor new technological advances to assist teams in reducing technical debt and adopt the right tooling.
• Collaborate with Data Governance and AI teams to continuously improve architecture governance practices.
• Develop and maintain policies, standards, and guidelines to ensure a consistent framework is applied across the data platform.
• Identify discrepancies between the technical architecture, agreed practices, and system designs proposed by project teams.
• Ensure architectures adhere to data compliance frameworks (e.g., GDPR, CCPA) and ethical considerations in AI/ML model deployment.
• Collaborate with Product Managers and Data Product Owners to enable Data as a Product, ensuring they are designed for reusability, scalability, and self-service consumption.
• Define best practices for the development, maintenance, and lifecycle management of data products.
• Act as a hands-on mentor to Data Engineering and Analytics teams, guiding them on day-to-day data modeling patterns, best practices, and execution choices.
• Advise business and technical stakeholders on self-service data platform capabilities to maximize value.
• Partner with IT team members to ensure architecture aligns with security strategy and policies.
• Drive continuous improvement and help drive the adoption of new data tools and practices.

Data Architect

Security Engineer

• Lead and Maintain the IT Compliance Program
• Ensure Regulatory and Industry Standards Compliance
• Support Business Processes
• Provide Strategic Guidance
• Deliver IT Compliance Reporting
• Implement AI-Powered Compliance Operations

Senior AI/ML Engineer

Data Architect

IT Security Compliance Lead