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

Junior AI Native Software Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- Java
2d
Software Engineer (DevOps) - Site Reliability
Revolut —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
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Amino & 24i —Madrid, Madrid provincia
- Trabajo híbrido
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- SQL
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Solicitud rápida
10d
Data Engineer (f/m/d)
Axpo —Madrid, Madrid provincia
- Jornada completa
- Español
- Azure
- Informática
Aircraft Networking & Connectivity Systems Engineer
Airbus Defence and Space SAU —Getafe, Madrid provincia
- Jornada completa
- Trabajo híbrido
- C++
- Python
AI Full Stack Software Engineer
IQVIA —Madrid, Madrid provincia
- Azure
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Software Engineer P2P (100% Remote, Worldwide)
Tether Operations Limited —Madrid, Madrid provincia
- Jornada completa
- Teletrabajo
- Inglés
- Grado
1d
Planning Engineer. Data Center
Aldesa —Madrid, Madrid provincia
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- Español
- Inglés
- Grado
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Senior Software Engineer Java, Kotlin and Python (All Genders)
zooplus SE —Madrid, Madrid provincia
- De 45.400 € a 68.000 € al año
- Jornada completa
- Trabajo híbrido
- Oracle
- DevOps
- Inglés
Solicitud rápida
Data Engineer
Kyndryl —Madrid, Madrid provincia
- Jornada completa
- Español
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7d
Data Scientist - Fraud Detection
Prima —Madrid, Madrid provincia
- Trabajo híbrido
- SQL
- AWS
- Machine learning
- Teletrabajo opcional
- Abono gimnasio
Solicitud rápida
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DCS EASYWARE —Madrid, Madrid provincia
- Trabajo híbrido
- Inglés
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Instrumentation and Control Engineer
Dapin —San Sebastián de los Reyes, Madrid provincia
- Inglés
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Systems Developer Engineer, Security Integrations Group
Amazon EU SARL (Spain Branch) —Madrid, Madrid provincia
- Jornada completa
- DevOps
- Sistema operativo Windows
- Java
Head of Engineering - Options
Keyrock —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- SQL
- C++
- Reclutamiento
Cloud Solution Consultant
OJC Consulting —Madrid, Madrid provincia
- Informática
- Sistemas ERP
- Inglés
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Fullstack Developer
UST —Madrid, Madrid provincia
- Trabajo híbrido
- Oracle
- DevOps
- Inglés
- Abono gimnasio
#BECA AHE - AI Strategy Lead - Engineering Transformation
Airbus Helicopters España, SA —Getafe, Madrid provincia
- Jornada completa
- Doctorado
- Informática
- Java
Senior/Lead Machine Learning Engineer
IFS —Madrid, Madrid provincia
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- DevOps
Solicitud rápida
Desktop Full-Stack Software Developer
The Reuse Company —Madrid, Madrid provincia
- Jornada completa
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Junior AI Native Software Engineer

Accenture -
Madrid, Madrid provincia

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Detalles del empleo

Jornada completa
Hace 2 días

Cualificaciones

CI/CD
Azure
Derecho
Informática
CSS
Microsoft SQL Server
NoSQL
Java
Máster
Arquitectura de microservicios
SQL
AWS
Docker
Grado
JavaScript
SDKs
APIs
Agile
Cloud
Inteligencia artificial
Python
Debugging
HTML

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.

Key Responsibilities

Use AI coding assistants daily as a standard part of delivery, actively, frequently, and with demonstrable impact on productivity and output quality
Integrate LLM APIs into applications in production: calling AI provider APIs in live code, managing token limits and latency, and building initial abstraction layers
Apply AI across the full software delivery lifecycle: AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks
Own the quality of AI-generated outputs in your delivery scope, exercise engineering judgment about reliability, limitations, and failure modes; know when AI output is production-ready and when it is not
Define and track KPIs to evaluate the effectiveness and ROI of AI-assisted workflows; present AI productivity and quality metrics to project stakeholders
Own delivery end-to-end — from design through to production support — in Agile sprint cycles alongside client engineering teams
Contribute to shared knowledge bases, reusable components, and internal AI tooling standards that benefit the wider team
Build and integrate the application layers, APIs, and interfaces that connect full-stack systems to agentic backends — understanding data flows, context handoffs, and integration points between your code and AI pipelines

Basic Qualifications

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field
Comercial software engineering experience in production environments (or equivalent demonstrated through academic projects, internships, or shipped personal projects)
Proficiency in at least one primary backend language: Python, Java, or TypeScript
Demonstrated hands-on experience using AI tools actively in day-to-day engineering work — with practical examples of how AI was used to solve real problems, iterate on outputs, and improve delivery; including direct experience calling LLM APIs in production code with an understanding of token management, latency, and cost tradeoffs
Basic understanding of web technologies including JavaScript, HTML, and CSS
Familiarity with cloud fundamentals (AWS, Azure, or GCP), containers (Docker), and CI/CD pipelines
Understanding of Agile delivery fundamentals
Experience with databases — SQL or NoSQL
Ability to validate, evaluate, and improve AI-generated outputs; understanding of AI limitations and responsible use

#LI-EU

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database engineer empleos en madrid, md

Junior AI Native Software Engineer

Software Engineer (DevOps) - Site Reliability

Full Stack Engineer

Data Engineer (f/m/d)

Aircraft Networking & Connectivity Systems Engineer

AI Full Stack Software Engineer

Software Engineer P2P (100% Remote, Worldwide)

Planning Engineer. Data Center

Senior Software Engineer Java, Kotlin and Python (All Genders)

Data Engineer

Data Scientist - Fraud Detection

Level 2 Support & Maintenance Engineer

Instrumentation and Control Engineer

Systems Developer Engineer, Security Integrations Group

Head of Engineering - Options

Cloud Solution Consultant

Fullstack Developer

#BECA AHE - AI Strategy Lead - Engineering Transformation

Senior/Lead Machine Learning Engineer

Desktop Full-Stack Software Developer

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

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