Senior AI Platform Engineer​/AI Architect - Microsoft Technologies

Position: Senior AI Platform Engineer / AI Architect - Microsoft Technologies
We're looking for a Senior AI Platform Engineer / AI Architect to join our team in the Netherlands in a hybrid working mode. In this role, you will design and build production-grade AI systems on Microsoft Azure while enabling engineering teams to adopt AI-native software engineering practices. This is a hands-on role that involves coding, infrastructure-as-code (IaC), CI/CD pipelines, test automation, observability and ensuring operational readiness s position is ideal for a senior engineer with deep experience in cloud-native engineering who is now focused on GenAI, RAG, agents, Git Hub Copilot, AI gateways, evaluation and platform automation.

Unlike conceptual or short-term assignments, this role allows you to contribute to enterprise AI transformation programs that impact real business workflows such as engineering productivity, intelligent automation and enterprise delivery.

You’ll work closely with architects, engineers, Git Hub/Microsoft specialists and client delivery teams on solutions that require both speed and production discipline. This role goes beyond basic API integrations and involves designing AI agent architectures, implementing evaluation frameworks, securing delivery pipelines and establishing robust governance. The focus is on real enterprise AI delivery, not isolated prototypes—building systems that can be tested, deployed, monitored, secured and transitioned for operational use.

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 Git Hub Copilot, Git Hub Actions, Git Hub 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 work streams such as retrieval, orchestration, AI gateways or Copilot enablement

Mentor engineers, review code and support architecture decisions for AI-assisted engineering adoption

Requirements6+ years of experience in software engineering, cloud engineering, Dev Ops or platform engineering

Hands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automation

Proven coding skills in Python, Type Script, 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

Nice to have

Deep knowledge of Microsoft Foundry, Azure OpenAI, Azure AI Search and related Azure AI services

Experience with Git Hub tool chains including Copilot, Git Hub Actions, Advanced Security and MCP-based integrations

Practical knowledge of RAG implementations: hybrid search, embeddings, semantic ranking and evidence capture

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