7 publicaciones de empleo destacadas de technical lead java en pozuelo de alarcón, md (¡Están contratando!)

AI - Software Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Azure
- Informática
- Java
AI Architect Engineer
Accenture —Madrid, Madrid provincia
- Jornada completa
- Java
- Máster
- APIs
Big Data Architect
Solera —La Moraleja, Madrid provincia
- Desde 40.000 € al año
- Jornada completa
- Trabajo híbrido
- Azure
- Informática
- Inglés
AI Application Architect
Avanade —Madrid, Madrid provincia
- Azure
- DevOps
- Java
Expert Manager, Software Engineering (Full Stack)
Bain & Company Inc —Lisboa
- Jornada completa
Principal Software Engineer - QuantumBlack, AI by McKinsey
McKinsey & Company —Madrid, Madrid provincia
- Español
- Azure
- Inglés
Manager I, Engineering - Code Coverage
Datadog —Madrid, Madrid provincia
- De guardia
- Oficina
- Java
Solicitud rápida

Related jobs to explore

Based on your search for technical lead java

Full Stack Engineer (Java/React)- Hybrid Madrid
UST —Madrid, Madrid provincia
You understand DevOps concepts, including Continuous Integration (CI) and Continuous Deployment (CD), and the importance and value of automated testing.
Solicitud rápida
Tech Lead BPM
Babel —Madrid, Madrid provincia
En Babel te acompañamos en tu camino hacia el éxito. Conocimientos en tecnologías frontend como JavaScript, HTML y CSS.

Quiero recibir la alerta de empleo más reciente de technical lead java en pozuelo de alarcón, 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

technical lead java jobs near pozuelo de alarcón, md

Empleos de Full Stack Developer en Lisboa

Empleos de Software Engineer en Madrid, Madrid Provincia

Empleos de Ai Internship en Barcelona, Barcelona Provincia

Empleos de Big Data Architect en Remoto, España

Empleos de Data en Guipúzcoa Provincia

Empleos de Practicas Data Science en Madrid, Madrid Provincia

Empleos de Data Analyst en Spain Remote

Empleos de Big Data Architect en 41005 Sevilla, Sevilla Provincia

Empleos de Big Data Architect en Barcelona, Barcelona Provincia

Empleos de Big Data Architect en Bilbao, Madrid Provincia

Empleos de Engineering Manager en Madrid Provincia

Empleos de Manager en Vitoria Gasteiz, Álava Provincia

Empleos de Embedded Software Engineer en Barcelona, Barcelona Provincia

Empleos de Artificial Intelligence Ai Engineer en Barcelona, Barcelona Provincia

Empleos de Data Engineer en A Coruña Provincia

Empleos de Ingeniero Software Junior en Madrid, Madrid Provincia

Empleos de Software Architect en Valencia, Valencia Provincia

Empleos de Practicas Software en Valencia, Valencia Provincia

Empleos de Cívica Software en Granada, Granada Provincia

Empleos de Full Time en Pombal

AI - Software Engineer

Accenture -
Madrid, Madrid provincia

Solicitar ahora

Detalles del empleo

Jornada completa

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.

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
Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required

#LI-EU

Solicitar ahora

Refina tu búsqueda

technical lead java empleos en pozuelo de alarcón, md

AI - Software Engineer

AI Architect Engineer

Big Data Architect

AI Application Architect

Expert Manager, Software Engineering (Full Stack)

Principal Software Engineer - QuantumBlack, AI by McKinsey

Manager I, Engineering - Code Coverage

Related jobs to explore

Quiero recibir la alerta de empleo más reciente de technical lead java en pozuelo de alarcón, md

Related Searches

Explorar empleos en más ubicaciones

Basic Qualifications

Herramientas para candidatos

Herramientas para empresas

Buscar

Mantener la conexión