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

AI Engineer
Sabio Group —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Azure
- Inglés
- Seguro de vida
- Plan de pensiones
Solicitud rápida
AI Engineer
Once For All - Nalanda —Madrid, Madrid provincia
- De 40.000 € a 65.000 € al año
- Trabajo híbrido
- Español
- Inglés
- Máster
13d
DevOps Engineer CI/CD
dLocal —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- DevOps
- Scripting
- Inteligencia artificial
Solicitud rápida
Senior Software Engineer - Finance & Compliance
FeverUp —Madrid, Madrid provincia
- De 50.000 € a 75.000 € al año
- Teletrabajo
- Español
- Inglés
- SQL
Solicitud rápida
Software Engineer
Pluxee —Madrid, Madrid provincia
- Jornada completa
- Español
- DevOps
- Inglés
Senior Backend Engineer
Once For All - Nalanda —Madrid, Madrid provincia
- De 40.000 € a 65.000 € al año
- Trabajo híbrido
- Español
- Azure
- Java
AI Staff Engineer
FeverUp —Madrid, Madrid provincia
- Inglés
- Máster
- SQL
Solicitud rápida
AI - Software Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- Java
Backend Engineer (AI Integration) 100% (f/m/d)
Julius Baer —Madrid, Madrid provincia
- Jornada completa
- Informática
- DevOps
- Inglés
Principal Engineer
SGS —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- AWS
- Python
Solicitud rápida
Backend Engineer
Dcycle —Madrid, Madrid provincia
- Trabajo híbrido
- DevOps
- SQL
- AWS
Senior Product Engineer / AI Solution Architect
SCH Banco Santander, S.A. —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Español
- Azure
- Informática
- Abono gimnasio
- Seguro de vida
12d
Senior Backend Engineer (.NET, Cloud & APIs)
Nextlane —Madrid, Madrid provincia
- Disponibilidad fin de semana
- Trabajo híbrido
- Azure
- DevOps
- Inglés
Fullstack Engineer
Destinus —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- DevOps
- Java
- AWS
Solicitud rápida
Senior Backend Engineer
FeverUp —Madrid, Madrid provincia
- De 50.000 € a 75.000 € al año
- Español
- Inglés
- SQL
Solicitud rápida
Senior/Staff Product Engineer
FeverUp —Madrid, Madrid provincia
- Teletrabajo
- Español
- Inglés
- Máster
Solicitud rápida
Senior/Lead Machine Learning Engineer
IFS —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- DevOps
Solicitud rápida
MLOps Engineer - Agentic Platform
NN Group —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Inglés
- AWS
- Parking gratuito
- Seguro de vida
Senior AI Architect - Microsoft Technologies (relocation to the Netherlands)
EPAM Systems, Inc. —Madrid, Madrid provincia
- Azure
- DevOps
- AWS
- Programa de recomendación
- Plan de pensiones
16h
AI Native Product Engineer & Orchestrator
Accenture —Madrid, Madrid provincia
- Jornada completa
- Java
- APIs
- Inteligencia artificial

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AI Engineer

Sabio Group -
Madrid, Madrid provincia

Solicitud rápida

Detalles del empleo

Jornada completa

Beneficios

Seguro de vida
Plan de pensiones

Cualificaciones

CI/CD
Español
Azure
Node.js
Derecho
Git
Inglés
Sistema operativo Windows
Máster
AWS
Respuesta a incidencias
Docker
JavaScript
Desarrollo de Back-End
Agile
Cloud
Inteligencia artificial
Recopilación de requisitos
Python

Descripción completa del empleo

Description

At Sabio Group, we're building the next generation of AI-powered customer experience for some of the world's most demanding enterprise brands — the kind of frontier customers who set the bar for what "great CX" looks like. We pair frontier-class large language models with deep contact centre expertise to deliver agentic experiences that materially improve containment, CSAT and operational efficiency.

We're hiring an AI Engineer to join our customer service bot / AI agent team in Madrid. You'll work end-to-end across the lifecycle — discovery, design, build, evaluate, deploy, operate — engineering robust LLM/NLU solutions, knowledge pipelines and integrations across voice and digital channels, primarily in Spanish.

This is a hands-on engineering role for someone who is curious about where AI is going, comfortable shipping agentic systems into production, and thoughtful about doing so safely and cost-effectively.

Key Responsibilities

Discovery & Design

Translate CX and business needs into AI solution designs spanning NLU/LLM, RAG, ASR/TTS and back-end integrations.
Define functional and non-functional requirements: latency, resiliency, observability, security, cost-per-conversation.

Agent & Model Implementation

Design and build agentic AI solutions — single-agent, multi-agent, tool-using and orchestrated patterns — using modern frameworks and frontier models.
Build and optimise NLU/LLM components: classification, NER, summarisation, RAG over enterprise knowledge bases.
Engineer prompts, tool schemas, context windows and token budgets for accuracy, latency and cost.
Develop data and knowledge pipelines for ingestion, cleansing, PII redaction and evaluation datasets.

Evaluation & Quality

Build evaluation harnesses (offline eval sets, LLM-as-judge, regression suites, A/B testing) and treat eval as a first-class deliverable, not an afterthought.
Drive continuous improvement via conversation analytics, error triage and failure-mode analysis.

LLMOps & Operations

Implement CI/CD for models and prompts, with feature flags, canary releases and rollback.
Track experiments, lineage, and model/prompt versions.
Operate services in production against SLOs with monitoring, tracing, alerting and incident response.

Responsible AI

Apply practical guardrails for safety, bias, hallucination, prompt-injection and jailbreak resistance.
Enforce GDPR / LOPDGDD: consent, minimisation, retention, access control, auditability.

Collaboration

Work alongside conversation designers, software engineers, data scientists, QA and Ops.
Produce clear design docs, runbooks and stakeholder updates.

Skills Knowledge and Expertise

Required

Hands-on experience delivering conversational AI — voicebots, chatbots or virtual assistants — including conversational flows, open-ended interactions, NLU and generative AI.
Production experience building agents with generative AI: agentic architectures (single-agent, multi-agent, tool/function-calling, planner–executor patterns), RAG, and orchestration.
Working knowledge of frontier LLM providers and platforms — e.g. Anthropic Claude, OpenAI, Google Gemini, Amazon Bedrock, Microsoft Azure AI — and a practical sense of when to use which.
Strong prompt engineering and context engineering skills across multiple LLM families, including system prompt design, structured output, and grounding strategies.
An evaluation mindset: you measure agent quality with eval sets, traces and metrics — not vibes.
Awareness of AI ethics, bias and safety, with practical experience mitigating them in deployed systems.
Token, latency and cost optimisation — model routing, caching (incl. prompt caching), context compression, retrieval tuning — as a core engineering discipline.
Comfort with agentic development workflows — using AI coding assistants and AI co-work / pair-development models (Claude Code, Copilot, Cursor or equivalent) as part of your day-to-day delivery.
Solid software engineering fundamentals: Python and/or JavaScript/Node, Git, IDEs, Agile delivery.
Customer-facing skills: requirements gathering, design, validation and stakeholder communication.
Working proficiency in Spanish and English.

Desirable

Cloud services, primarily AWS, with containerised deployment via Docker / Kubernetes.
Contact centre integrations (e.g. Genesys, Avaya, Cisco, Amazon Connect) and Meta / WhatsApp Business / digital channel integrations.
Experience with ASR/TTS and voice-specific concerns: barge-in, turn-taking, ASR error recovery, latency budgets.
Speech/NLU recognition models and continuous-improvement loops (Microsoft STT, MS CLU, Google, Amazon).
Observability for LLM systems: tracing, eval pipelines, online quality monitoring.
Familiarity with emerging agent interoperability standards (e.g. MCP, A2A) and human-in-the-loop / escalation patterns.
Microsoft Bot Framework, Genesys Dialog Engine or VXML exposure.
Consulting experience analysing existing bot estates, evaluating KPIs (containment, CSAT, AHT, transfer rate) and recommending improvements.

Nice to Have

Exposure to Google Conversational Agent / Playbooks or DialogFlow — useful if you've worked with it, but not required.

Benefits

This is your chance to join and friendly and passionate team that will motivate you to learn and develop your career in the company.

Benefits may include:

Pension Scheme
Remote/Flexible work
Life insurance
Health insurance
25 days paid holiday a year
LinkedIn Learning
Plus many more! (Benefits are dependant on your base location.)

The Small Print

Strictly No Agencies; any submission of resumes without prior request from Sabio Group will not be deemed as an introduction and therefore will not warrant an introduction fee. All applicants must have the right to work in the territory to which the role relates (UK & EU). Sabio Group are unable to offer sponsorship on any roles advertised.

About Sabio Group

THE DIGITAL CX TRANSFORMATION COMPANY

Why Sabio?

We bring together expertise in cloud migration, cutting-edge CX technologies and powerful customer insight to deliver exceptional end-to-end customer experiences.

At Sabio, we are devoted to creating a community of inclusion, and an environment free from discrimination, harassment, and retaliation.

We are committed to being an equal opportunity employer that not only values but celebrates diversity and inclusion. We firmly stand against discrimination based on factors such as race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, and disability status.

If you need accommodations, additional support and/or have any specific requirements, we invite you to reach out to our talent team directly: [email protected]

Solicitud rápida

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