We're looking for a Senior AI Architect to join our team in the Netherlands in a hybrid working mode.

In this role, you will help clients design and scale production-grade AI platforms and solutions on Microsoft Azure.

You will work at the intersection of enterprise architecture, cloud-native engineering, Git

Hub-enabled software delivery and responsible AI adoption.

This position focuses on shaping large-scale AI transformation programs that connect business outcomes with practical architecture design.

You will engage in areas such as Azure AI platforms, copilots, RAG, agentic systems, governance, observability, evaluation, security and Responsible AI practices.

Unlike roles centered on proofs of concept, this opportunity involves delivering enterprise-grade AI systems embedded into real workflows, including engineering productivity, knowledge retrieval, automation and AI-enabled delivery.

The challenges go beyond basic API calls and span AI-native software engineering, Git

Hub Copilot integration, secure architectures, Fin

Ops and will collaborate with architects, engineers, Microsoft/Git

Hub specialists and client leadership teams to drive secure and governed AI adoption.

Responsibilities

Define target-state architectures for AI platforms, assistants, RAG systems, agents, AI gateways and AI-native engineering workflows

Lead architecture discovery, maturity assessments, technical roadmaps, platform decisions and delivery governance

Design Azure-first architectures using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure API Management, AKS, Azure Functions, Application Insights, Azure Monitor, Key Vault, Microsoft Entra ID, Cosmos DB, PostgreSQL and Microsoft Fabric where applicable

Design AI-native engineering systems using Git

Hub Copilot, Git

Hub Enterprise, Git

Hub Advanced Security, agent-ready repositories, secure pull-request practices and AI-assisted delivery patterns

Design harnesses around AI systems,



including agent instructions, tool contracts, MCP integrations, retrieval grounding, evaluation suites, telemetry, cost controls, policy controls and human approval gates

Define governance and operational frameworks for Responsible AI, security, identity, Fin

Ops and observability

Translate business outcomes into target architecture, executive narratives, platform decisions and delivery governance across client leadership, architecture, engineering and security teams

Facilitate workshops, hackathons and enablement sessions focused on AI adoption, Copilot integration and engineering excellence

Convert practical experience into reusable patterns, accelerators and architectural blueprints

Mentor architects and engineers and contribute to presales and solution design initiatives

Requirements10+ years in solution architecture, cloud platforms or platform engineering

Strong experience with enterprise AI, GenAI, agentic systems, RAG and AI-native engineering

Proficiency with Microsoft Azure and modern cloud-native architecture

Knowledge of Git

Hub workflows (CI/CD, Dev

Ops, IaC) and secure engineering practices

Track record of moving AI initiatives beyond PoC to enterprise-grade production environments

Hands-on capability to validate prototypes, review code and guide engineering decisions

Ability to explain how to make AI useful in production, not just impressive in a demo

Capability to design platform architecture, governance models, adoption plans and AI delivery workflows

Confidence working across enterprise realities, leveraging Azure and Git

Hub pragmatically





Strong communication skills with both executives and technical stakeholders

Nice to have

Experience with Git

Hub Copilot Enterprise adoption, AI-native SDLC transformation, Git

Hub Actions and Git

Hub Advanced Security

Familiarity with agent frameworks such as Semantic Kernel, Lang

Chain, Lang

Graph, Auto

Gen, Llama

Index, CrewAI or similar

Knowledge of Microsoft 365 Copilot, Copilot Studio, Microsoft Graph, Teams, Share

Point or Power Platform integration

Understanding of AI gateways, model routing, semantic caching, model abstractions, usage telemetry and AI Fin

OpsBackground in enterprise infrastructure with Terraform/IaC, Kubernetes/AKS, CI/CD and secure API gateway practices

Awareness of agent reliability and security techniques, including workflow state, recovery, tool-permission boundaries, evaluation gates, prompt-injection defense, audit trails, rollback mechanisms and human approval workflows

Familiarity with compliance and governance standards such as GDPR, EU AI Act readiness or ISO/IEC 42001Experience in regulated industries such as finance, healthcare, energy, retail, manufacturing or public sector

Knowledge of other AI ecosystems, including AWS Bedrock, Google Vertex AI, Databricks, Snowflake, Anthropic, OpenAI API or Hugging Face

We offer26 paid holiday days

Pension plan scheme

Disability insurance (WGA Shortfall insurance)Long-term disability insurance (WIA Top up insurance)EPAM Employee Stock Purchase Plan (ESPP)Commuting to work - costs reimbursement

Laptop + corporate simcard + corporate mobile device (subject to certain eligibility requirements)Bike lease

Employee Assistance Program

Corporate Programs including Employee Referral Program with rewards

Learning and development opportunities including in-house training and coaching, professional certifications, and courses #J-18808-Ljbffr

📌 Senior AI Architect - Microsoft Technologies (relocation to the Netherlands) (España)
🏢 EPAM Systems
📍 España