AI Solutions Lead

Bleckmann is a market leader in supply chain management (SCM) services for fashion and lifestyle brands. Established in 1862, Bleckmann has evolved from a transportation company into a provider of complete supply chain solutions, with specific expertise in e-fulfillment. With a strong base in Europe, the company has expanded to the U.S. and Asia, enabling Bleckmann to serve customers worldwide. Thanks to our investments and extensive experience in IT solutions, we offer a unified platform to our clients across the globe.

With approximately 6,500 team members, we work every day to support our customers and deliver on their promises. With a turnover of €626 million, Bleckmann has the scale and flexibility to provide world-class solutions. Would you like to be part of our dynamic team and contribute to our growing success?

The Team

You will be part of the Business Development group and reporting directly to the Chief Business Development Officer. Our mission is to uncover and predict trends, patterns, and opportunities across new and existing clients. The insights we generate are critical for informed decision-making and are delivered through dashboards and analytical reports.

To support the expansion of our AI capabilities, we are looking for an AI Solutions Lead to deliver and expand a high-impact lead classification and scoring model in co execution with an external partner. This role marks the beginning of building a strong internal AI practice, and you will be central in both owning the existing model and steering future AI initiatives across our business development organization.

Your Responsibilities

As the AI Solutions Lead, you will be responsible for the ownership, enhancement, and integration of our AI models into production environments. You will collaborate closely with BI, Analysts, Engineers, and Business Stakeholders within business development to ensure the continued relevance and performance of the AI solutions.

You will:

• Lead and maintain the delivery of an AI-based lead classification and scoring model that is co-created with an external party.
• Ensure model performance through validation, retraining, and deployment best practices.
• Translate business goals into machine learning use cases and AI-powered solutions.
• Coordinate with internal teams to integrate and expand the model into business processes and data pipelines.
• Act as a key driver for scaling AI adoption in other parts of the business.
• Identify, prioritize, and lead additional AI and ML initiatives across the organization.
• Ensure ethical and compliant AI usage aligned with data governance and quality standards.
• Present insights and progress to technical and non-technical stakeholders.
• Take ownership of an existing AI lead scoring/classification model delivered by consultants.
• Monitor, validate, and enhance model performance through regular retraining and optimization
• Expansion of model with new features by managing and coordinating data and engineering experts.
• Ensure integration of the model into data pipelines and business processes.

Scope of Authority:

• Authorized to manage the full model lifecycle including changes, improvements, and deployment strategies.
• Make decisions on retraining cycles, feature engineering, and model evaluation metrics.

Performance Indicators:

• Model accuracy and business alignment (e.g., improved conversion rates or lead quality).
• Reduction in manual lead qualification efforts.
• Timely delivery of updates and enhancements.

Cross-Functional Collaboration & Business Alignment (25%)
Activities:

• Collaborate with Data Engineers, Analysts, and Business Stakeholders to deliver and align model outcomes with business goals.
• Translate business requirements into AI/ML problems and vice versa.
• Present findings and recommendations to both technical and non-technical audiences.

Scope of Authority:

• Empowered to represent AI capabilities in cross-functional meetings.
• Lead conversations around feasibility, business value, and prioritization of AI solutions.

Performance Indicators:

• Stakeholder satisfaction with AI solution outcomes.
• Successful integration of model insights into sales and marketing operations.
• Frequency and quality of knowledge transfer sessions or presentations.

Driving AI Strategy & Innovation (25%)
Activities:

• Identify and lead new AI/ML initiatives within the organization, with a dominant focus on new business and client retention.
• Promote the use of best practices in AI development, governance, and ethical considerations.
• Evaluate and experiment with new tools (e.g., AutoML, MLOps platforms).

Scope of Authority:

• Authorized to propose and prototype AI solutions aligned with strategic goals.
• Lead discussions on model governance, scalability, and long-term roadmap.

Performance Indicators:

• Number and impact of new AI initiatives successfully piloted or launched.
• Alignment of AI strategy with company priorities.
• Development of center of expertise on AI & governance within the organization

Adherence to AI governance and quality…