Lead AI Consultant

Key Responsibilities

1. Client-Facing Consulting & Delivery

• Act as primary consultant on AI engagements advising senior client stakeholders onAItransformation strategyAIarchitecture and implementation.
• Develop AI strategies solution concepts and technical specifications calibrated to each clients organisational realitynot templated frameworks applied regardless of context.
• Translate business requirements into technical specifications and technical constraints into language stakeholders can act on. Both directions matter equally.
• Facilitate client workshops fromAIdiscovery through implementation planning; contribute to pitches and business development as a subject matter expert.

2. Strategic Foresight & Scenario Thinking

• Anticipate how AI will reshape organisational structures information flows and decision-making over the next two to five years advising clients with concrete time-bound roadmaps.
• Build forward-looking scenarios that connect emerging capabilities (agentic systems real-time retrieval autonomous workflows) to concrete operational change.
• Challenge inherited assumptions about hierarchies and operating models. Propose AI-native alternatives grounded in feasibility and organisational readiness.

3. Internal Enablement & Workforce Transformation

• Support &Leadin-house training and enablement programmes from week one designing materials calibrated from foundational concepts to advanced agentic workflow design.
• Serve as a visible example of AI-first practice. Cultural change does not come from slide decks; it comes from colleagues who work differently and produce better results.

4. AI Practice & Solution Architecture

• Contribute to the design of AI solutions agent orchestration retrieval-augmented generation multi-agent coordination strategically and structurally not only at implementation level.
• Evaluate and operationalise new AI tools frameworks and platforms as they emerge. The expectation is a live understanding of the state of the art not last quarters releases.
• Support Merkles service lines with AI-native expertise integrating new paradigms into delivery rather than siloing them in a separate innovation function.

5. Ecosystem Building

• Sustain partnerships with startups university research groups and open-source communities. The frontier of applied AI does not live inside large organisations alone.
• Help organise technical hackathons and experimentation sprints designed to test ideas before they reach client engagements.

Requirements:

• Degree inBusiness Information SystemsComputer Science Data or a closely related technical discipline. An engineering foundation is non-negotiable.
• Several years of experience in AI consulting software engineering or data with direct client interaction and delivery accountability.
• Professional fluency in Englishis mandatory and German a nice to have.
• Strategic foresight over reactive execution. You see where AI is heading and think infuturescenarios.Anconsultantwho lives in the present however skilled is not the person we are looking for.

• AI-first orientation. Every workflow begins with the question: can AI do this and if so how You default to yes unless evidence compels otherwise.

• Deep practical literacy. Generative AI tools coding assistants agentic frameworks used daily not experimentally. You maintain current proficiency as the ecosystem evolves week by week.

• Empathy and communicative precision. Technical capability without the ability to listen understand client constraints and build trust is insufficient.

• Self-directed prioritisation. You manage your workload without waiting to be told what matters.

• A drive to learn that does not depend on external motivation. If the pace of change feels like disruption rather than opportunity this role will not suit you.

Nice to have:

• Prior consulting client-facing technical advisory or forward-deployed engineering experience.
• Hands-on experience with agent orchestration frameworks LLM integration or AI-native product development.
• Track record of facilitating workshops or guiding clients through structured discovery.
• Familiarity with global professional services organisations.

About this challenge:

This is not an incremental hire into an established team. We are building something new and early hires will shape what it becomes.

• Strategic influence within one of the largest digital transformation networks globally.
• Direct access to enterprise clients across industries with autonomy to shape how AI adoption unfolds inside those organisations.
• An environment engineered for rapid growth: dedicated experimentation time state-of-the-art tooling collaboration with leading practitioners.
• Competitive compensation flexible working arrangements and the operational backing of Dentsus global infrastructure.