Principal AI Consultant; m​/f​/d

Principal AI Consultant (m/f/d)
About Us

We are a specialist consulting firm delivering services and solutions in “Everything Data” – Business Intelligence, Advanced Analytics, Big Data & Cloud, and Web & Mobile Applications. We are part of a strategic alliance with Synvert, a group of six successful full-service Data & Analytics (D&A) consulting firms, with a clear goal to become one of EMEA’s largest D&A consulting companies.

Our services are based on the latest market-leading enterprise technology platforms, and delivered by a dynamic team of expert consultants. Our strength lies in our ability to efficiently deliver customer insight and value, gained through our decades of experience with real-world challenges.

As a Principal AI Consultant you'll be responsible for leading complex end-to-end Artificial Intelligence engagements, driving the definition, architecture, delivery, and adoption of high-impact AI solutions. The role combines deep expertise in AI, machine learning, and software engineering with strong leadership and consulting capabilities. The Principal Artificial Intelligence Consultant provides direction on solution design, delivery strategy, and technical standards, ensuring that AI solutions are scalable, reliable, maintainable, and aligned with business objectives.

• Lead complex Artificial Intelligence engagements from opportunity shaping and problem framing to solution delivery, deployment, and adoption
• Guide the design and implementation of production-grade AI solutions, includingsolution architecture,models, AI applications, APIs, orchestration layers, pipelines, and platform integrations
• Bring structure to ambiguous business challenges by defining scope, requirements, execution plans, technical approaches, and expected value
• Ensure delivery excellence through strong engineering standards, code quality expectations, testing approaches, observability, monitoring, and operationalgovernance
• Drive key technical and functional decisions across modelling, application architecture, scalability, reliability, security, and maintainability
• Manage and influence technical and business stakeholders, building trust andidentifyingopportunities foradditionalvalue creation
• Coach and guide team members across project delivery, technical problem solving, and solution quality
• Contribute to reusable assets, delivery methodologies, technical standards, and best practices across the Artificial Intelligence practice
• Present strategic recommendations, delivery progress, and technical outcomes ina clear way, translating complexity into business impact
• Build and strengthen client relationships,identify growth opportunities within existing accounts, and contribute to new business development
• Contribute to recruitment activities, including candidate evaluation, interviews, and support throughout the hiring process
• Mentor senior team members and help develop leadership, delivery, and technical capabilities across the practicewithin project delivery
• Represent the Artificial Intelligence team in internal and external initiatives, promoting its capabilities, impact, and continuous growth

• Degree in Computer Science, Engineering, Statistics, or related field
• + 7 years of experience in Data Science or AI roles
• +2 years of experience leading teams and managing end-to-end project delivery
• Proven experience delivering AI/ ML solutions in production environments
• Strong e xperience leading end-to-end project delivery, technical design, and stakeholder management in client-facing environments

• Expert programming skills in Python and strong hands-on experience with AI / ML frameworks and production AI ecosystems
• Deep understanding of Statistics, Machine Learning, Artificial Intelligence, and the design of production-grade intelligent systems
• Strong expertise in architecting and delivering scalable AI applications, including APIs, services, pipelines, orchestration, deployment, and monitoring
• Strong software engineering knowledge covering architecture patterns, code quality, testing strategy, CI/CD, observability, resilience, security, and long-term maintainability
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