Descripción de la oferta
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 governance at scale. You 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 Open AI, Azure AI Search, Azure API Management, AKS, Azure Functions, Application Insights, Azure Monitor, Key Vault, Microsoft Entra ID, Cosmos DB, Postgre SQL 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, Gen AI, 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, Ia C) and secure engineering practices Track record of moving AI initiatives beyond Po C 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, Crew AI 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 Ops Background in enterprise infrastructure with Terraform/Ia C, 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 42001 Experience 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, Open AI 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
