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

EPAM Systems, Inc.; Bellprat; Híbrido; EUR 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Pension plan

Disability insurance

Long-term disability insurance

ESPP

Laptop + corporate devices

Bike lease

Learning and certifications

Commute cost reimbursement

Employee Assistance Program

Corporate programs

Descripción de la vacante

EPAM Systems, Inc. seeks a Senior AI Platform Engineer/AI Architect to design and build production-grade AI systems in a hybrid Netherlands setting. You will implement Azure AI technologies and create scalable, observable AI workflows for client teams.

The role emphasizes hands-on development, governance, and enterprise delivery, with mentoring of engineers and collaboration with architects and specialists.

Formación

• 6+ years in software/cloud engineering, DevOps or platform engineering.
• Hands-on GenAI, RAG, and AI platform automation experience.
• Proven production coding in Python/TypeScript/C#/Java/Go for APIs and services.
• Strong Azure and cloud-native architecture experience; IaC expertise.

Responsabilidades

• Build RAG pipelines, AI assistants, agent workflows and AI gateway components.
• Deliver AI-native engineering workflows using GitHub Copilot/Actions and secure PR patterns.
• Create CI/CD pipelines, IaC automation, observability stacks and deployment frameworks.
• Mentor engineers and guide AI-assisted SDLC with governance and quality.

Conocimientos

GenAI

RAG

Agentic systems

Copilots

AI platform automation

Python

TypeScript

C#

Java

Go

Azure

Kubernetes

IaC

CI/CD

Security & observability

Mentoring

Herramientas

Microsoft Foundry

Azure OpenAI

Azure AI Search

Azure Functions

AKS / Azure Container Apps

Cosmos DB

GitHub Copilot / GitHub Actions

Descripción del empleo

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 at scale.This position is ideal for a senior engineer with deep experience in cloud-native engineering who is now focused on GenAI, RAG, agents, GitHub 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, GitHub/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.ResponsibilitiesBuild RAG pipelines, AI assistants, agent workflows, AI gateway components, MCP-based integrations and reusable platform elementsImplement 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 toolsDeliver AI-native engineering workflows using GitHub Copilot, GitHub Actions, GitHub Advanced Security and secure pull-request patternsApply harness engineering patterns for AI systems, including agent instructions, tool contracts, retrieval grounding, evaluation suites, telemetry, safety checks, cost tracking and human approval gatesBuild CI/CD pipelines, IaC automation, observability stacks and deployment frameworks for AI workloadsCreate reusable templates, reference implementations, demos and onboarding kits for client teamsOwn one or more implementation workstreams such as retrieval, orchestration, AI gateways or Copilot enablementMentor engineers, review code and support architecture decisions for AI-assisted engineering adoptionRequirements6+ years of experience in software engineering, cloud engineering, DevOps or platform engineeringHands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automationProven coding skills in Python, TypeScript, C#, Java or Go for production-grade APIs, back-end services and infrastructure automationStrong experience with Microsoft Azure and cloud-native architecturesKnowledge of containers, Kubernetes, serverless models and Infrastructure-as-Code practicesFamiliarity with security, identity, logging, monitoring, cost optimization and operational readiness principlesAbility to demonstrate production-ready AI systems: tested, deployed, monitored and supported at scalePractical experience mentoring teams and guiding AI-assisted SDLC with quality and governance in mindStrong communication and collaboration skills adaptable to both technical and business environmentsNice to haveDeep knowledge of Microsoft Foundry, Azure OpenAI, Azure AI Search and related Azure AI servicesExperience with GitHub toolchains including Copilot, GitHub Actions, Advanced Security and MCP-based integrationsPractical knowledge of RAG implementations: hybrid search, embeddings, semantic ranking and evidence captureFamiliarity with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangChain, AutoGen and similarStrong programming skills in multiple languages (Python, TypeScript, C#, Java, Go)Experience in evaluation and agent reliability engineering: golden datasets, regression tests, prompt-injection defense, state handling, retries, recovery and feedback loopsExposure to Microsoft 365 Copilot integrations (Graph, Teams, SharePoint, Power Platform)Familiarity with other AI ecosystems like AWS Bedrock, Google Vertex AI, Databricks, Anthropic, Hugging Face or SnowflakeWe offer26 paid holiday daysPension plan schemeDisability insurance (WGA Shortfall insurance)Long-term disability insurance (WIA Top up insurance)EPAM Employee Stock Purchase Plan (ESPP)Commuting to work - costs reimbursementLaptop + corporate simcard + corporate mobile device (subject to certain eligibility requirements)Bike leaseEmployee Assistance ProgramCorporate Programs including Employee Referral Program with rewardsLearning and development opportunities including in-house training and coaching, professional certifications, and courses