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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Automat-it - **Location:** Madrid, Spain - **Salary:** €40,000.0 - €60,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Continuous Integration, DevOps, Amazon DynamoDB, Identity and Access Management, Python (Programming Language), Machine Learning, Open Source Technology, Software Deployment, Speech Recognition, Core Voice Platform, AWS Cdk, Large Language Models, Multi-Agent Systems, Backend, Cloudformation, Kubernetes, Low Latency, Speech Synthesis, Functional Programming, Cloudwatch, Terraform, Serverless Computing, Docker - **Published:** August 1, 2026 - **Apply:** https://www.adzuna.es/contact-us.html ## About the Role + Operate in a fast-paced, project-based environment where you may own a project as the main engineer + Strong hands-on experience building and deploying AI / GenAI systems in production + Strong hands-on AWS experience beyond model invocation, including infrastructure, IAM, serverless services, networking, storage, monitoring, and production deployments using Amazon Bedrock. + Experience building RAG systems in practice, including retrieval logic, vector databases, and output quality improvements + Strong understanding of modern LLM ecosystems, including commercial and open-source models, their trade-offs, deployment options, and production use cases. + Strong Python skills and a good understanding of backend system design + Experience designing multi-agent systems or more complex orchestration workflows + Experience with vector databases (OpenSearch, pgVector, Pinecone, etc.) + Comfort working in fast-moving environments with short project cycles (weeks to a few months) + Strong communication skills and ability to work directly with clients and cross-functional teams + Ability to clearly explain technical decisions, limitations, and trade-offs in English (written and spoken) + Hands-on experience with Amazon Bedrock Knowledge Bases, AgentCore, Agents, AWS Strands, or MCP is a strong advantage. + Experience selecting, evaluating and optimizing LLMs for quality, latency and cost. + Ability to explain technical trade-offs and guide customers through AI solution design is a strong advantage. + Experience with Infrastructure as Code (Terraform, CloudFormation or AWS CDK), Docker, Kubernetes and CI/CD pipelines is a strong advantage. + Experience with speech-to-text, text-to-speech or Voice AI is an advantage. + Background in Machine Learning or Data Science (including model training or fine-tuning) - an advantage Automat-it is committed to fostering a workplace that promotes equal opportunities for all. We firmly believe that cultivating a diverse workforce is crucial to our success. Our recruitment decisions are grounded in your experience and skills, recognizing the value you bring to our team. ## Description + Build and deliver production-ready GenAI systems on AWS, including Amazon Bedrock, AgentCore, RAG systems, intelligent document processing, voice AI, and LLM-powered services. + Design and implement AI agents using Amazon Bedrock AgentCore, AWS Strands, MCP, and modern orchestration frameworks for real customer solutions. + Work closely with Solution Architects, DevOps, and customer teams to turn discovery workshops, ideas, and POCs into production-ready AI systems. + Evaluate and select the most appropriate LLMs based on accuracy, latency, cost, and customer requirements. + Build reusable AI components and deployment patterns that accelerate future customer projects. + Deploy, monitor, and improve ML/LLM systems in production, focusing on performance, cost, and reliability + Work with AWS services such as Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch + Adapt existing ML or GenAI code into production environments when needed + Continuously improve system quality, including retrieval performance, output consistency, and evaluation approaches ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Agentic AI - From Theory to Practice: Developing Multi-Agent AI Systems on Azure](https://www.wearedevelopers.com/videos/1532-agentic-ai-from-theory-to-practice-developing-multi-agent-ai-systems-on-azure) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)