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

EPAM Systems, Inc.; Dublin; Hybrid; EUR 90,000 - 140,000; Full time

Benefits offered by this job

26 paid holiday days

Pension plan

Disability insurance

Long-term disability (WIA)

ESPP

Commuting reimbursement

Laptop + SIM

Bike lease

EAP

Training & certifications

Job summary

EPAM Systems, Inc. in the Netherlands is seeking a Senior AI Platform Engineer/AI Architect to design production-grade AI systems on Azure, enabling AI-native software engineering across teams. This hands-on role involves coding, IaC, CI/CD, observability and governance for enterprise-scale AI delivery.

You will work on RAG pipelines, AI assistants, gateway components and reusable platform elements, with strong emphasis on secure, tested deployments and operational readiness at scale.

Qualifications

• 6+ years in software/cloud engineering or platform engineering.
• Hands-on GenAI, RAG and AI platform automation experience.
• Proficient in Python, TypeScript, C#, Java or Go for production APIs.
• Strong Azure cloud-native architecture knowledge.
• Experience with containers, Kubernetes and IaC.
• Security, logging, monitoring, cost optimization, operation readiness.

Responsibilities

• Build RAG pipelines, AI assistants, agent workflows and gateways.
• Deliver AI-native engineering workflows using GitHub tools.
• Implement CI/CD, IaC, observability and deployment frameworks.
• Create reusable templates and onboarding kits for client teams.
• Mentor engineers and guide AI-assisted SDLC with governance.

Skills

GenAI & RAG

AI platform automation

Python

TypeScript

C#

Java

Go

Azure cloud

IaC

CI/CD pipelines

Security & governance

Mentoring teams

Tools

Azure Foundry

Azure OpenAI

Azure AI Search

AKS

Cosmos DB

Key Vault

Azure Functions

API Management

GitHub Actions

GitHub Copilot

Job description

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