Senior AI Platform Engineer/AI Architect - Microsoft Technologies (relocation to the Netherlands)

Job summary

Senior AI Platform Engineer/AI Architect to design and build production-grade AI systems on Microsoft Azure in a hybrid working mode.

Qualifications

• 6+ years of experience in software engineering, cloud engineering, DevOps or platform engineering
• Hands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automation
• Proven coding skills in Python, TypeScript, C#, Java or Go for production-grade APIs, back-end services and infrastructure automation
• Strong experience with Microsoft Azure and cloud-native architectures
• Knowledge of containers, Kubernetes, serverless models and Infrastructure-as-Code practices
• Familiarity with security, identity, logging, monitoring, cost optimization and operational readiness principles
• Ability to demonstrate production-ready AI systems: tested, deployed, monitored and supported at scale
• Practical experience mentoring teams and guiding AI-assisted SDLC with quality and governance in mind
• Strong communication and collaboration skills adaptable to both technical and business environments

Responsibilities

• Build RAG pipelines, AI assistants, agent workflows, AI gateway components, MCP-based integrations and reusable platform elements
• Implement Azure AI solutions using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Functions, Azure API Management, AKS, Azure Container Apps, Key Vault, Cosmos DB and monitoring tools
• Deliver AI-native engineering workflows using GitHub Copilot, GitHub Actions, GitHub Advanced Security and secure pull-request patterns
• Apply harness engineering patterns for AI systems, including agent instructions, tool contracts, retrieval grounding, evaluation suites, telemetry, safety checks, cost tracking and human approval gates
• Build CI/CD pipelines, IaC automation, observability stacks and deployment frameworks for AI workloads
• Create reusable templates, reference implementations, demos and onboarding kits for client teams
• Own one or more implementation workstreams such as retrieval, orchestration, AI gateways or Copilot enablement
• Mentor engineers, review code and support architecture decisions for AI-assisted engineering adoption

Skills

Relocation