Vertex AI Engineer
Location: Veghel, Netherlands
6-12 months contract (Extendable)
Rate: 450 Euros/day
Must have Technical Skills:
• Build and manage Grounding configurations — Google Search grounding and custom data source grounding via Vertex AI Agent Builder for factual, up-to-date responses.
• Design multi-modal AI applications leveraging Gemini 2.0+ capabilities — text, image, audio, video, and document inputs within a single unified model call.
• Implement AI agent evaluation frameworks — using Vertex AI Evaluation Service (AutoSIA, BLEU, ROUGE, custom metrics) to assess agent quality before production deployment.
• Configure and manage Vertex AI Endpoints with traffic splitting, canary deployments, and autoscaling for production-grade model serving SLAs.
• Use Vertex AI Model Evaluation and Vertex AI Experiments for A/B testing between model versions (champion/challenger) with statistically significant evaluation datasets.
• Implement AI safety controls — configure Vertex AI Safety Filters (harm categories, thresholds), input/output sanitization, and PII detection for enterprise-grade Gemini deployments.
• Apply AI governance frameworks — EU AI Act compliance considerations, model cards, data lineage documentation, and bias evaluation using Vertex Explainable AI (SHAP values, feature attributions).
• Manage Generative AI token cost governance — implement token budgeting, prompt length optimization, caching strategies (Vertex AI Context Caching), and per-application quota enforcement. Strong experience with: Google Cloud
• Google Cloud Platform (GCP)
• Vertex AI
• Vertex AI Studio
• Gemini Models
• Vertex AI Agent Builder
• Vertex AI Model Garden
• Vertex AI Pipelines Programming
• Python
• SQL
• REST APIs
• FastAPI / Flask AI / ML
• Machine Learning fundamentals
• Generative AI
• LLMs
• Prompt Engineering
• RAG
• Embeddings
• Vector Search
• Fine-tuning Data Engineering
• BigQuery
• Cloud Storage
• Data Pipelines
• Feature Engineering
• BigQuery ML (BQML)
• Dataplex
• Cloud Spanner / Firestore
• Dataflow
• AlloyDB for PostgreSQL MLOps
• CI/CD • Docker • Kubernetes • Model Deployment • Monitoring • ML Lifecycle Management AI Frameworks • LangChain • LangGraph
• Google ADK (Agent Development Kit) • TensorFlow / PyTorch Architecture • AI Solution Design • Agentic AI Architecture
•Responsible AI
• Scalability & Performance Optimization Experience Range –10-12 years in IT Org. and strong experience in data science, data engineering, AI/ML .
5+ years as AI Engineer to set up and implement AI Solution including governance.
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