AI Engineer
Context
Role Overview
We are looking for an AI Engineer responsible for designing building integrating and operationalizing AI solutions in production environments.
The role focuses on implementing concrete AI use cases (not defining the AI strategy) working closely with existing systems and development teams.
Key Responsibilities
AI Solution Development
- Translate business needs into production-ready AI features
- Build solutions for use cases such as document processing classification summarization information extraction and intelligent assistants
- Work with LLMs generative AI retrieval-augmented systems (RAG) and open-source frameworks (e.g. Hugging Face LangChain LlamaIndex)
System Integration
- Integrate AI components into existing applications APIs and backend systems (-based environments)
- Ensure secure maintainable and well-governed integrations (access control validation auditing)
Evaluation & Quality
- Define and execute evaluation strategies (accuracy grounding hallucinations consistency bias)
- Improve prompts retrieval logic and output structures based on test results
Production & Monitoring
- Move AI prototypes into production-ready services
- Implement CI/CD versioning monitoring logging and observability (latency usage cost errors)
- Ensure reliability performance and cost control in production
Collaboration
- Work closely with developers architects security and business stakeholders
- Document solutions limitations and operational considerations
- Share best practices for responsible AI usage
Required Skills
- Strong Python (AI services backend integration retrieval pipelines)
- Good knowledge of C# / .NET (API integration system collaboration)
- Experience with generative AI and LLM-based applications
- Knowledge of retrieval-augmented generation (RAG) embeddings vector databases (nice to have)
- Experience with APIs system integration and SQL/data processing
- Understanding of AI evaluation prompt engineering and structured outputs
- Familiarity with CI/CD containerization and production deployments (nice to have)
- Awareness of AI governance bias explainability and security considerations
- Experience with logging/monitoring tools (e.g. OpenTelemetry Dynatrace is a plus)
Profile
- Hands-on pragmatic and delivery-focused
- Strong analytical mindset with attention to quality and risks
- Ownership of technical implementation in assigned use cases
- Good communication skills in a multidisciplinary environment
- Proactive in improving AI solution quality and reliability
- Quick learner in evolving AI technologies
Languages
- Dutch or French (one required)
- Understanding of the second national language is a plus
Working Model
- Hybrid (2 days onsite 3 days remote per week)
Engagement Type
- Freelance or employee (via staffing/detachment structure)
AI Engineer Context Role Overview We are looking for an AI Engineer responsible for designing building integrating and operationalizing AI solutions in production environments. The role focuses on implementing concrete AI use cases (not defining the AI strategy) working closely with existing syste...
AI Engineer
Context
Role Overview
We are looking for an AI Engineer responsible for designing building integrating and operationalizing AI solutions in production environments.
The role focuses on implementing concrete AI use cases (not defining the AI strategy) working closely with existing systems and development teams.
Key Responsibilities
AI Solution Development
- Translate business needs into production-ready AI features
- Build solutions for use cases such as document processing classification summarization information extraction and intelligent assistants
- Work with LLMs generative AI retrieval-augmented systems (RAG) and open-source frameworks (e.g. Hugging Face LangChain LlamaIndex)
System Integration
- Integrate AI components into existing applications APIs and backend systems (-based environments)
- Ensure secure maintainable and well-governed integrations (access control validation auditing)
Evaluation & Quality
- Define and execute evaluation strategies (accuracy grounding hallucinations consistency bias)
- Improve prompts retrieval logic and output structures based on test results
Production & Monitoring
- Move AI prototypes into production-ready services
- Implement CI/CD versioning monitoring logging and observability (latency usage cost errors)
- Ensure reliability performance and cost control in production
Collaboration
- Work closely with developers architects security and business stakeholders
- Document solutions limitations and operational considerations
- Share best practices for responsible AI usage
Required Skills
- Strong Python (AI services backend integration retrieval pipelines)
- Good knowledge of C# / .NET (API integration system collaboration)
- Experience with generative AI and LLM-based applications
- Knowledge of retrieval-augmented generation (RAG) embeddings vector databases (nice to have)
- Experience with APIs system integration and SQL/data processing
- Understanding of AI evaluation prompt engineering and structured outputs
- Familiarity with CI/CD containerization and production deployments (nice to have)
- Awareness of AI governance bias explainability and security considerations
- Experience with logging/monitoring tools (e.g. OpenTelemetry Dynatrace is a plus)
Profile
- Hands-on pragmatic and delivery-focused
- Strong analytical mindset with attention to quality and risks
- Ownership of technical implementation in assigned use cases
- Good communication skills in a multidisciplinary environment
- Proactive in improving AI solution quality and reliability
- Quick learner in evolving AI technologies
Languages
- Dutch or French (one required)
- Understanding of the second national language is a plus
Working Model
- Hybrid (2 days onsite 3 days remote per week)
Engagement Type
- Freelance or employee (via staffing/detachment structure)
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