Senior AI Engineer (AWS Bedrock)

Automat-it; Madrid; Hybrid; EUR 65,000 - 100,000; Full time

Job summary

Automat-it is hiring an AI Engineer to build production-grade GenAI systems on AWS, focusing on RAG pipelines, agent-based workflows, and LLM-backed services. You will own projects end-to-end from design to deployment, collaborating with startup Data Science and R&D teams.

The role is hybrid from Madrid, requiring strong Python skills, AWS expertise, and the ability to deliver reliable AI solutions in fast-paced client environments.

Qualifications

• Experience building and deploying GenAI systems in production.
• Hands-on AWS experience including infrastructure, IAM, serverless, networking, storage, monitoring, and Bedrock deployments.
• Experience building RAG systems with retrieval logic, vector databases, and output quality improvements.
• Strong understanding of modern LLM ecosystems and deployment options; familiarity with both commercial and open-source models.
• Strong Python skills and backend system design knowledge.
• Experience designing multi-agent systems or complex orchestration workflows.
• Experience with vector databases (OpenSearch, pgVector, Pinecone, etc.).
• Ability to work in fast-moving environments with short project cycles; strong communication with clients and cross-functional teams.

Responsibilities

• Build and deliver production-ready GenAI systems on AWS (Bedrock, AgentCore, RAG, document processing, voice AI).
• Design and implement AI agents using Bedrock AgentCore, AWS Strands, MCP and orchestration frameworks.
• Collaborate with Solution Architects, DevOps and customer teams to turn ideas into production AI systems.
• Evaluate LLMs for accuracy, latency, cost, and customer requirements.
• Create reusable AI components and deployment patterns for future projects.
• Deploy and monitor ML/LLM systems in production focusing on performance and reliability.
• Work with AWS services (Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, CloudWatch).
• Adapt existing ML/GenAI code to production environments; improve retrieval and evaluation.

Skills

GenAI systems

AWS infra

RAG systems

Python

Multi-agent design

English communication

Client collaboration

CI/CD pipelines

Tools

Amazon Bedrock

AgentCore

OpenSearch

SageMaker

CloudWatch

Lambda

DynamoDB

S3

Terraform

CloudFormation

AWS CDK

Docker

Kubernetes

Pinecone

Job description

Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for an AI Engineer (Senior level or strong Middle) to join our team and work directly with startup's Data Science and R&D teams. This is a hands-on, delivery-focused role where you will own projects end-to-end, from early design to production deployment.

The role is focused on building production-grade Generative AI systems on AWS, especially RAG pipelines, agent-based workflows, and LLM-powered backend services. This is not a pure research or model training role, it’s about designing and shipping reliable systems under real constraints.

Work location: hybrid from Madrid.

Curious about what it's really like to work at Automat-it?

Explore our benefits, culture, and what success in your first year could look like here.

Key Responsibilities

• 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
• Operate in a fast-paced, project-based environment where you may own a project as the main engineer

Requirements

• 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.