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

AI Architect Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Java
- Máster
- APIs
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
20h
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
1d
AI - Software Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- Java
IT Digital Application Support Engineer – Web & Mobile Platforms
Radisson Hotel Group —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- DevOps
Solicitud rápida
Director of Product Management - Data Streaming
HiveMQ GmbH —Madrid, Madrid provincia
- De 120.000 € a 154.000 € al año
- Jornada completa
- Teletrabajo
- Controladores lógicos programables
- Manufactura
Solicitud rápida
AI Native Product Engineer & Orchestrator
Accenture —Madrid, Madrid provincia
- Jornada completa
- Java
- APIs
- Inteligencia artificial
AI Platform Engineer (m/f/d)
BASF —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- DevOps
Senior Network & Edge Security Engineer
dLocal —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- DevOps
- Inglés
Solicitud rápida
AI Engineer
Sabio Group —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Azure
- Inglés
- Seguro de vida
- Plan de pensiones
Solicitud rápida
Senior Backend Engineer (.NET, Cloud & APIs)
Nextlane —Madrid, Madrid provincia
- Disponibilidad fin de semana
- Trabajo híbrido
- Azure
- DevOps
- Inglés
Senior Data Platform Engineer (SnowFlake/Azure) - Remote
UST —Alcorcón, Madrid provincia
- Teletrabajo
- Azure
- Informática
- Ventas
- Abono gimnasio
Solicitud rápida
Senior Tech Generalist (Software Engineer)
Capchase —Madrid, Madrid provincia
- Horas extra
- APIs
Senior Backend Engineer
FeverUp —Madrid, Madrid provincia
- De 50.000 € a 75.000 € al año
- Español
- Inglés
- SQL
Solicitud rápida
Senior Site Reliability Engineer (SRE)
Sparta —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- Oficina
- Java
- AWS
3d
Backend Engineer (AI Integration) 100% (f/m/d)
Julius Baer —Madrid, Madrid provincia
- Jornada completa
- Informática
- DevOps
- Inglés
Senior Rust Engineer - High Frequency Trading (HFT)
Keyrock —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- AWS
- Scripting
- Reclutamiento
4d
Backend Software Engineer – Microservices (Java)
GMV —Tres Cantos, Madrid provincia
- Trabajo híbrido
- Java
- APIs
- Seguro dental
Google Data and AI Specialist
BIP - Business Integration Partners —Madrid, Madrid provincia
- Jornada completa
- Español
- Informática
- DevOps
Technical Lead - Core Applications - London or Madrid
Sonnedix —Madrid, Madrid provincia
- Jornada completa
- Informática
- Inglés
- APIs
1d

Quiero recibir la alerta de empleo más reciente de cloud observability engineer en madrid, md

Al iniciar sesión en tu cuenta, aceptas las Condiciones del servicio de SimplyHired, nuestra Política sobre cookies y nuestra Política de privacidad.

Explorar empleos en más ubicaciones

cloud observability engineer jobs near madrid, md

Empleos de Technical Lead en Madrid, Madrid Provincia

Empleos de QA Engineer en Madrid, Madrid Provincia

Empleos de Software Engineer en Madrid, Madrid Provincia

Empleos de Back End Developer en Madrid, Madrid Provincia

Empleos de Platform Engineer en Madrid, Madrid Provincia

Empleos de Java Developer en Tres Cantos, Madrid Provincia

Empleos de Application Support Engineer en Madrid, Madrid Provincia

Empleos de Junior Data Engineer en Madrid, Madrid Provincia

Empleos de Data Engineer en Galicia

Empleos de Technical Lead en Madrid Provincia

Empleos de Technical Recruiter en Madrid, Madrid Provincia

Empleos de Lead en Murcia Provincia

Empleos de Technical Lead en Barcelona, Barcelona Provincia

Empleos de Technical Product Manager en Sant Joan Despí, Barcelona Provincia

Empleos de Technical Lead en Barcelona Provincia

Empleos de Ai Internship en Barcelona, Barcelona Provincia

Empleos de Qa Engineer en En Remoto

Empleos de Qa Engineer en Sant Andreu De La Barca, Barcelona Provincia

Empleos de Network Engineer en Madrid Provincia

Empleos de Lead Engineer en San Sebastián De Los Reyes, Madrid Provincia

AI Architect Engineer

Accenture -
Madrid, Madrid provincia

Solicitar ahora

Detalles del empleo

Jornada completa

Cualificaciones

CI/CD
Derecho
Java
Máster
Arquitectura de microservicios
Docker
Terraform
SDKs
APIs
Cloud
Inteligencia artificial
Python
Debugging

Descripción completa del empleo

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You are

An AI Native Engineer with a strong foundation in building cloud-native solutions and hands-on experience designing and deploying agentic systems, especially for enterprise environments. You’re a critical thinker who thrives in ambiguity, delivering concrete results by designing, building, and running AI agents that augment workflows and scale across modern infrastructure.

You'll shape how enterprises adopt AI-native engineering - either by leading complex agentic solutions and developing engineering talent, or by owning critical technical areas end-to-end as a senior IC

The Work

You’ll partner directly with client stakeholders — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be net-new platforms and systems that need to be stitched together in our clients’ environments alongside our ecosystem partners.

Agent Architecture & Engineering

Design and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Implement resilient, testable, and maintainable agentic workflows that can be iterated on quickly.

AI Platform Integration

Develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement.
Contribute to shared libraries, SDKs, and patterns that can be reused across clients.

Cloud-Native Engineering

Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable AI-native systems.
Own deployment, monitoring, and troubleshooting for your services in production.

Domain-Specific Workflows

Tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints.
Work closely with client SMEs to translate business workflows into agentic solutions.

Client Engagement

Participate in and/or lead design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
Communicate trade-offs, risks, and recommendations clearly to both technical and non-technical audiences.

Measure & Improve

Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
Iterate rapidly based on data, feedback, and changing requirements.

Knowledge Sharing

Craft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps.
Contribute to internal communities of practice around AI-native and agentic engineering.

Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements.

Job Description
Job Description
We are:
A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.
You are
An AI Native Engineer with a strong foundation in building cloud-native solutions and hands-on experience designing and deploying agentic systems, especially for enterprise environments. You’re a critical thinker who thrives in ambiguity, delivering concrete results by designing, building, and running AI agents that augment workflows and scale across modern infrastructure.
You'll shape how enterprises adopt AI-native engineering - either by leading complex agentic solutions and developing engineering talent, or by owning critical technical areas end-to-end as a senior IC
The Work
You’ll partner directly with client stakeholders — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be net-new platforms and systems that need to be stitched together in our clients’ environments alongside our ecosystem partners.
Agent Architecture & Engineering
Design and build enterprise-ready AI agents incorporating retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Implement resilient, testable, and maintainable agentic workflows that can be iterated on quickly.
AI Platform Integration
Develop and/or extend abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and multi-provider enablement.
Contribute to shared libraries, SDKs, and patterns that can be reused across clients.
Cloud-Native Engineering
Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability stacks to deliver scalable AI-native systems.
Own deployment, monitoring, and troubleshooting for your services in production.
Domain-Specific Workflows
Tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints.
Work closely with client SMEs to translate business workflows into agentic solutions.
Client Engagement
Participate in and/or lead design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
Communicate trade-offs, risks, and recommendations clearly to both technical and non-technical audiences.
Measure & Improve
Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
Iterate rapidly based on data, feedback, and changing requirements.
Knowledge Sharing
Craft reusable patterns, documentation, and best practices that influence internal assets and client roadmaps.
Contribute to internal communities of practice around AI-native and agentic engineering.
Travel may be required for this role. The amount of travel will vary from 25% to 75% depending on business need and client requirements.
Job Qualifications
Job Qualifications
Key Responsibilities
- Architect and govern production-grade agentic systems at enterprise scale: multi-agent orchestration across complex environments, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability
- Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable
- Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance as standard design practice across providers including OpenAI, Anthropic, Vertex AI, and open-source models
- Own LLMOps at programme scale: eval strategy, prompt governance, observability tooling standards, safety monitoring and cost controls across multiple concurrent systems
- Lead client engineering engagements at senior level — facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams
- Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements
- Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms to senior client stakeholders
Basic Qualifications
- Strong software engineering experience in production environments
- Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable
- Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level
- Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs
- RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering
- LLMOps fundamentals: eval harness design, prompt versioning, and production observability
- Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)
- Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience
- Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure
- People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversation
#LI-MP

Solicitar ahora

Refina tu búsqueda

cloud observability engineer empleos en madrid, md

AI Architect Engineer

IT Cloud & Automation Engineer - Remoto

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

AI - Software Engineer

IT Digital Application Support Engineer – Web & Mobile Platforms

Director of Product Management - Data Streaming

AI Native Product Engineer & Orchestrator

AI Platform Engineer (m/f/d)

Senior Network & Edge Security Engineer

AI Engineer

Senior Backend Engineer (.NET, Cloud & APIs)

Senior Data Platform Engineer (SnowFlake/Azure) - Remote

Senior Tech Generalist (Software Engineer)

Senior Backend Engineer

Senior Site Reliability Engineer (SRE)

Backend Engineer (AI Integration) 100% (f/m/d)

Senior Rust Engineer - High Frequency Trading (HFT)

Backend Software Engineer – Microservices (Java)

Google Data and AI Specialist

Technical Lead - Core Applications - London or Madrid

Quiero recibir la alerta de empleo más reciente de cloud observability engineer en madrid, md

Related Searches

Explorar empleos en más ubicaciones

Key Responsibilities

Basic Qualifications

Herramientas para candidatos

Herramientas para empresas

Buscar

Mantener la conexión