AI Strategy & Implementation Consultant
DWI Consulting Ltd
Ghent, Belgium
2 days ago
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Ghent, Belgium
Tech stack
Artificial Intelligence
Software Applications
Google BigQuery
Databases
Memory Management
Machine Learning
Search Technologies
Systems Integration
Google Cloud Platform
Multi-Agent Systems
Prompt Engineering
Generative AI
Data Strategy
Gsuite
Virtual Agents
Api Management
Web Api
Job description
Our customer is looking to further advance in AI-driven automation to enhance operational efficiency across key business functions. They have established a modern cloud-first technology platform using Google's ecosystem and are building internal AI engineering capabilities. We are looking for a consulting expert who can bridge the gap between business strategy and technical implementation-someone who can work alongside their engineering team to identify high-impact AI opportunities within each operational department and bring them to life quickly.
The tasks:
- Lead structured discovery sessions with different business units (Operations, Finance, HR, Sales, Procurement, etc.), dedicating focused engagement periods to each
- Assess business processes and pain points to uncover areas where intelligent automation can drive measurable value
- Architect and deliver AI-powered automation solutions leveraging the Google Cloud AI stack
- Take solutions from concept through testing to production, working either autonomously or with the internal AI team as needed
- Integrate Gemini capabilities with existing Google Workspace applications to unlock workflow automation
- Implement semantic search and knowledge retrieval patterns to ground AI agent responses in company data
- Configure autonomous agent behaviours including API calls, decision-making logic, and tool orchestration
- Work in Tandem with the organization's machine learning engineering team to achieve technical excellence
Requirements
- A minimum of 4 years working with enterprise AI initiatives, data strategy, or management consulting
- Deep hands-on experience with the Google Cloud Platform and its AI/ML service portfolio
- Demonstrated ability to architect, build, and deploy intelligent agents using Vertex AI and Agent Builder technologies
- Proficiency in prompt engineering and fine-tuning using Gemini model variants
- Practical experience integrating machine learning models with enterprise data infrastructure via BigQuery
- Knowledge of knowledge base patterns, embeddings, and similarity search for AI-powered applications
- Understanding of multi-step reasoning, agent orchestration, and intelligent workflow design
- Strong capability in understanding business processes and translating them into technical requirements
- Track record of identifying opportunities where AI can create competitive advantage
- Retrieval-Augmented Generation (RAG): Connecting agents to enterprise databases
- Function Calling/Extensions: API integrations and external system interactions
- Vector Search/Vertex AI Vector Search: Semantic search and memory management
- Agentic Workflows: Multi-agent systems and autonomous reasoning
Skills and Experience required:
- A minimum of 4 years working with enterprise AI initiatives, data strategy, or management consulting
- Deep hands-on experience with the Google Cloud Platform and its AI/ML service portfolio
- Demonstrated ability to architect, build, and deploy intelligent agents using Vertex AI and Agent Builder technologies
- Proficiency in prompt engineering and fine-tuning using Gemini model variants
- Practical experience integrating machine learning models with enterprise data infrastructure via BigQuery
- Knowledge of knowledge base patterns, embeddings, and similarity search for AI-powered applications
- Understanding of multi-step reasoning, agent orchestration, and intelligent workflow design
- Strong capability in understanding business processes and translating them into technical requirements
- Track record of identifying opportunities where AI can create competitive advantage
- Retrieval-Augmented Generation (RAG): Connecting agents to enterprise databases