Senior AI & Data Transformation Consultant

The most important things in a few sentences 

We are looking for a senior colleague to join our AI & Data team who can combine consulting expertise, architectural thinking, and hands-on delivery of AI/Data solutions. We are looking for someone who can lead discovery workshops with senior stakeholders, understand business problems, translate them into technical solution designs, and stay actively involved as solutions are built, validated, and adopted in practice.  

You will not be a purely managerial profile overseeing projects from a distance, nor a purely technical specialist without client interaction. Your role will be approximately 50% consulting and client shaping, 50% solution architecture and delivery leadership. It is important that you have demonstrable hands-on experience designing and delivering AI/Data solutions, ideally across the entire lifecycle from discovery through architecture, PoC/MVP, implementation, operations, and scaling.  

Our primary focus is the Microsoft ecosystem, including Azure AI, Azure OpenAI, Microsoft Fabric, Power Platform, Copilot, and related technologies. However, we take a technology-agnostic approach. Our clients drive AI and data initiatives across a variety of platforms, so experience with AWS, GCP, Databricks, Snowflake, open-source LLM stacks, RAG frameworks, or modern AI/Data platforms is highly valued.  

If you enjoy consulting, client engagement, presales, architecture, and at the same time want to help build a practical AI & Data capability with real impact on client projects, this role could be for you. 

Your Role in the Team 

You will be a senior member of the team helping clients move AI initiatives from ideas, workshops, and pilots into practical, secure, and scalable solutions. Specifically, you will:  

• Lead discovery and solution-shaping workshops with clients, ranging from C-level executives and business owners to IT, data, security, and delivery teams.  

• Identify and prioritize AI/Data use cases based on business value, feasibility, data readiness, risks, costs, and expected impact.  

• Translate business requirements into architectural and technical designs, from high-level solution concepts through target architecture, integration design, data requirements, governance, and implementation roadmaps.  

• Design enterprise AI/Data architectures, including GenAI solutions, LLM applications, RAG architectures, agentic workflows, ML models, AI-ready data platforms, APIs/integrations, security, monitoring, and operating models.  

• Contribute to presales and business development activities, including proposal development, RFP responses, effort estimation, solution design, client presentations, demos, and proof-of-concept scenarios.  

• Act as a trusted partner to delivery teams, collaborating with AI/ML engineers, data engineers, solution architects, developers, business analysts, change and adoption specialists, and other SMEs.  

• Provide delivery assurance, including architectural reviews, feasibility validation, technical and business trade-off assessments, scope prioritization, quality assurance, and alignment with measurable business outcomes.  

• Support clients with AI transformation and adoption, not as a full-time change manager, but as someone who understands that successful AI solutions require business ownership, governance, operating models, adoption, and value measurement.  

• Help shape and grow our AI & Data offering, including reusable assets, delivery playbooks, reference architectures, accelerators, and offerings around AI strategy, AI governance, AI-ready data foundations, GenAI/Agentic AI, and Copilot adoption. 

What Is Important to Us 

What you should bring:

• Proven experience designing and delivering AI/Data solutions. We are not looking for someone who only understands the terminology or has experience creating presentations. We need someone who can describe specific solutions they have worked on, explain their role in architecture and delivery, and discuss the decisions they helped make.  

• A consulting mindset and strong stakeholder management skills. You know how to facilitate workshops, structure ambiguous problems, ask the right questions, work with senior client stakeholders, and explain complex technical concepts in a way that business audiences can understand.  

• Architectural thinking. You can design end-to-end solutions, break them down into logical components, understand data and integration dependencies, and evaluate security, scalability, operability, costs, and risks.  

• Practical knowledge of AI/Data technologies. You do not need to be a full-time developer, but you must understand how AI/Data solutions are actually built, including data pipelines, cloud platforms, APIs, LLMs/GenAI, RAG, agentic approaches, ML models, governance, monitoring, evaluation, and operationalization.  

• The ability to connect business value with technical feasibility. You understand when AI makes sense, when automation or process change may be a better option, how to define success metrics, and what needs to be validated before investment decisions are made.  

• Experience with presales or business development. You can contribute to proposals, pricing, RFP responses, client presentations, and pilot/MVP design.  

• Professional-level English and the ability to operate effectively in Czech and Slovak client environments. 

What would be a major advantage:

• Experience with Microsoft technologies: Azure AI, Azure OpenAI, Microsoft Fabric, Power Platform, Copilot Studio, M365 Copilot, Azure DevOps.  

• Experience with additional platforms: AWS, GCP, Databricks, Snowflake, MLflow, LangChain, LlamaIndex, Vector Databases, Kubernetes, CI/CD.  

• Practical experience with GenAI / LLM solutions, RAG, agentic workflows, AI orchestration, LLM evaluation, guardrails, observability, or LLMOps/MLOps.  

• Experience in regulated or enterprise environments, such as financial services, insurance, telecommunications, energy, public sector, retail, pharmaceuticals, or manufacturing.  

• Knowledge of topics such as Responsible AI, AI Governance, EU AI Act, Model Risk Management, Data Privacy, Security by Design.  

• Experience with adoption, change management, AI upskilling, or operating model design.  

• Certifications such as Azure / AWS / GCP Architect, Azure AI Engineer, Databricks, TOGAF, Scrum / Product Owner are considered an advantage, but are not required.