3 publicaciones de empleo destacadas de cloud observability engineer en md (¡Están contratando!)

Senior AI Platform Engineer/AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
- Azure
- DevOps
- Java
- Programa de recomendación
- Plan de pensiones
7h
Senior AI Engineer
Trinetix —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Máster
- APIs
Solicitud rápida
8h
IT Cloud & Automation Engineer - Remoto
eXperience IT Solutions —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- Azure
- Java
- AWS
- Formación continua
- Oportunidades de crecimiento y desarrollo profesional
Solicitud rápida
2h

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Senior AI Platform Engineer/AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
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…
7h
Senior AI Engineer
Trinetix —Madrid, Madrid provincia
We are looking for a Senior AI Engineer to design and build production-grade AI applications and services using Python.
Solicitud rápida
8h

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

EPAM Systems, Inc. -
Madrid, Madrid provincia

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Detalles del empleo

Hace 7 horas

Beneficios

Programa de recomendación
Plan de pensiones

Cualificaciones

CI/CD
Azure
DevOps
C#
Java
Kernel
AWS
Desarrollo de Back-End
SharePoint
GitHub
APIs
Cloud
Inteligencia artificial
Python
SDLC

Descripción completa 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.

Responsibilities

Build RAG pipelines, AI assistants, agent workflows, AI gateway components, MCP-based integrations and reusable platform elements
Implement 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 tools
Deliver AI-native engineering workflows using GitHub Copilot, GitHub Actions, GitHub Advanced Security and secure pull-request patterns
Apply harness engineering patterns for AI systems, including agent instructions, tool contracts, retrieval grounding, evaluation suites, telemetry, safety checks, cost tracking and human approval gates
Build CI/CD pipelines, IaC automation, observability stacks and deployment frameworks for AI workloads
Create reusable templates, reference implementations, demos and onboarding kits for client teams
Own one or more implementation workstreams such as retrieval, orchestration, AI gateways or Copilot enablement
Mentor engineers, review code and support architecture decisions for AI-assisted engineering adoption

Requirements

6+ years of experience in software engineering, cloud engineering, DevOps or platform engineering
Hands-on experience with GenAI, RAG, agentic systems, copilots and AI platform automation
Proven coding skills in Python, TypeScript, C#, Java or Go for production-grade APIs, back-end services and infrastructure automation
Strong experience with Microsoft Azure and cloud-native architectures
Knowledge of containers, Kubernetes, serverless models and Infrastructure-as-Code practices
Familiarity with security, identity, logging, monitoring, cost optimization and operational readiness principles
Ability to demonstrate production-ready AI systems: tested, deployed, monitored and supported at scale
Practical experience mentoring teams and guiding AI-assisted SDLC with quality and governance in mind
Strong communication and collaboration skills adaptable to both technical and business environments

Nice to have

Deep knowledge of Microsoft Foundry, Azure OpenAI, Azure AI Search and related Azure AI services
Experience with GitHub toolchains including Copilot, GitHub Actions, Advanced Security and MCP-based integrations
Practical knowledge of RAG implementations: hybrid search, embeddings, semantic ranking and evidence capture
Familiarity with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangChain, AutoGen and similar
Strong 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 loops
Exposure 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 Snowflake

We offer

26 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

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cloud observability engineer empleos en md

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

Senior AI Engineer

IT Cloud & Automation Engineer - Remoto

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