AI Platform Engineer

h3Functie /h3 p1. Context and Objective /p pThe assignment is aimed at strengthening the AI Platform Team in the implementation, industrialisation and operational support of a standardised, secure, scalable and cost-efficient enterprise AI platform. /p pThe AI Platform Engineer is responsible for the hands-on implementation of reusable platform services for Generative AI, Retrieval Augmented Generation (RAG) and Agentic AI. /p pThe role translates defined architecture, standards and governance requirements into automated platform components that can be consumed by multiple development and platform teams. /p pThe focus is on generic platform capabilities, self-service, technical quality assurance and the controlled transition from proof of concept to production. /p p2.

Key Responsibilities
/p pAI Platform Engineering /p ulliImplement, configure and maintain enterprise AI platform services, with AWS Bedrock as the primary platform. /li /ul ul liIntegrate and manage approved foundation models, model endpoints, inference services, runtimes and supporting frameworks. /li liDevelop standardised APIs, SDKs, templates and reference implementations. /li liContribute to lifecycle management, versioning, compatibility and technical documentation. /li /ul pAgentic AI Integrations /p ul liDevelop reusable patterns for AI agents, tool use, planning and execution flows. /li liImplement and secure MCP servers and other standardised tool/service integrations. /li liDevelop agent templates covering identity propagation, authorisation, error handling, time-outs and audit logging. /li liPerform technical testing of agent reliability, security and predictability. /li /ul pRAG Platform Services /p ul liImplement generic retrieval and knowledge services for RAG applications. /li liIntegrate vector databases, knowledge bases, embedding services and retrieval components. /li liProvide standardised interfaces for document and data access, respecting access rights and data classification. /li liCollaborate with data engineers on data and knowledge pipelines. /li /ul pDevOps, Automation Self-Service /p ul liAutomate provisioning, configuration, deployment, testing and rollback using Infrastructure as Code and CI/CD. /li liDevelop and maintain Terraform modules and GitHub Actions workflows. /li liProvide paved-road workflows and self-service capabilities for onboarding teams and use cases. /li liIntegrate policy and quality controls into delivery pipelines. /li /ul pSecurity, Privacy Governance /p ul liImplement technical guardrails for prompt/output control, sandboxing, networking, data access and tool usage. /li liApply secrets management, key management, least privilege and encryption. /li liImplement policy-as-code, pre-deployment checks, audit logging and traceability. /li liSupport security, privacy and compliance assessments and remediation. /li /ul pObservability, Operations FinOps /p ul liSet up monitoring and tracing for model calls, agent actions, tool calls, errors, latency and platform availability. /li liWork with Dynatrace, OpenTelemetry, Langfuse and other AI observability solutions where applicable. /li liSupport incident, problem and change management, including root cause analysis. /li liMonitor and optimise AI platform and infrastructure costs. /li /ul p3. Required Technical Expertise /p ul liStrong experience in cloud and platform engineering within enterprise environments. /li liStrong practical knowledge of AWS and experience with Amazon Bedrock or comparable GenAI platforms. /li liStrong Python programming skills and experience with API/SDK development. /li liExperience with Generative AI, LLMs, RAG, embeddings, vector search and Agentic AI. /li liExperience with MCP, tool integrations or comparable standards is highly desirable. /li liExperience with Terraform, GitHub Actions, CI/CD, GitOps and automated quality controls. /li liKnowledge of containers, Kubernetes and preferably Amazon EKS. /li liKnowledge of IAM, secrets management, policy-as-code, logging, monitoring and OpenTelemetry. /li liExperience with Dynatrace, Langfuse, OpenSearch, LangGraph or LangChain is a plus. /li /ul p4. Required Competencies /p ul liTakes technical ownership and works independently within defined architecture and governance frameworks. /li liAnalytical and pragmatic problem-solving approach, with focus on reliability, security and time-to-value. /li liStrong collaboration skills in multidisciplinary teams. /li liEnablement-oriented mindset, focusing on reusable solutions rather than team-specific customisation. /li liAble to clearly document and communicate technical decisions, risks and dependencies. /li liGood communication skills in Dutch and English; French is a plus. /li /ul p5. Desired Profile /p ul liMinimum 5 years of relevant experience in cloud engineering, platform engineering, DevOps or a comparable technical domain. /li liProven experience building or managing production-ready shared platform services. /