6 publicaciones de empleo destacadas de cloud observability engineer en getafe, md (¡Están contratando!)

Senior AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
- Azure
- DevOps
- AWS
- Programa de recomendación
- Plan de pensiones
Software Delivery Associate
Getnet Platforms —Madrid, Madrid provincia
- Trabajo híbrido
- Español
- Informática
- DevOps
- Seguro dental
- Seguro de vida
Solicitud rápida
Senior Solutions Architect (Data & AI)
Kyndryl —Madrid, Madrid provincia
- Jornada completa
- Azure
- AWS
- APIs
Team Lead IT Operations (m/f/d)
Infront Financial Technology GmbH —Madrid, Madrid provincia
- Jornada completa
- Oracle
- DevOps
- Inglés
Google Data and AI Specialist
BIP - Business Integration Partners —Madrid, Madrid provincia
- Jornada completa
- Español
- Informática
- DevOps
Platform Engineer
Backbase —Madrid, Madrid provincia
- De guardia
- Inglés
- Desarrollo de software
- Python
Solicitud rápida

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Software Delivery Associate
Getnet Platforms —Madrid, Madrid provincia
It enables financial institutions, non-bank financial institutions, NBFIs, and payment service providers, PSPs, to operate, scale and evolve their payment…
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Senior AI Architect - Microsoft Technologies (relocation to the Netherlands)

EPAM Systems, Inc. -
Madrid, Madrid provincia

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Detalles del empleo

Beneficios

Programa de recomendación
Plan de pensiones

Cualificaciones

CI/CD
Azure
DevOps
Kernel
AWS
PostgreSQL
Terraform
SharePoint
GitHub
Cloud
Manufactura
Inteligencia artificial
SDLC

Descripción completa del empleo

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, GitHub-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, GitHub Copilot integration, secure architectures, FinOps and governance at scale.

You will collaborate with architects, engineers, Microsoft/GitHub 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 GitHub Copilot, GitHub Enterprise, GitHub 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, FinOps 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

Requirements

10+ 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 GitHub workflows (CI/CD, DevOps, 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 GitHub pragmatically
Strong communication skills with both executives and technical stakeholders

Nice to have

Experience with GitHub Copilot Enterprise adoption, AI-native SDLC transformation, GitHub Actions and GitHub Advanced Security
Familiarity with agent frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, LlamaIndex, CrewAI or similar
Knowledge of Microsoft 365 Copilot, Copilot Studio, Microsoft Graph, Teams, SharePoint or Power Platform integration
Understanding of AI gateways, model routing, semantic caching, model abstractions, usage telemetry and AI FinOps
Background 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 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, OpenAI API or Hugging Face

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 getafe, md

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

Software Delivery Associate

Senior Solutions Architect (Data & AI)

Team Lead IT Operations (m/f/d)

Google Data and AI Specialist

Platform Engineer

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