AI Engineer / LLM Engineer
About the role
We are looking for an AI Engineer to join a dynamic AI team within an international technology environment.
In this role, you will design, build, and deploy LLM-powered applications, RAG pipelines, multi-agent systems, and scalable AI solutions on AWS.
You will work at the intersection of software engineering, AI engineering, data pipelines, and cloud deployment, contributing to real use cases across the airline group. This role is highly hands-on and focused on building intelligent systems that move from experimentation to production.
You will collaborate closely with domain experts, Data Engineers, Product Managers, and a Tech Lead to translate business needs into reliable and scalable AI products.
If you enjoy working with LLMs, agents, RAG, vector databases, Python APIs, and AWS-native AI services, this could be a great fit.
What you'll do
Design, build, and maintain LLM-powered applications and multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, or similar
Develop and optimise RAG pipelines, including document ingestion, chunking strategies, embedding generation, retrieval logic, and vector search
Implement and manage vector databases such as pgvector on Aurora, OpenSearch, Pinecone, or similar
Build and maintain data and ETL pipelines using Apache Airflow, Prefect, or similar tools
Develop backend services and APIs in Python / FastAPI to serve AI models, RAG systems, and agent workflows
Deploy and manage AI workloads on AWS services such as Bedrock, SageMaker, Lambda, S3, Aurora/RDS, EC2
Work with Docker and Kubernetes to containerise and orchestrate AI workloads
Design and execute evaluation frameworks for LLM outputs, including automated testing, LLM-as-judge approaches, and human-in-the-loop review
Work with LLM APIs and orchestration tools such as AWS Bedrock, OpenAI API, Anthropic API, or similar
Apply prompt engineering, fine-tuning techniques, and LLM evaluation methodologies
Collaborate with domain experts, Data Engineers, Product Managers, and the Tech Lead to turn business requirements into AI solutions
Participate in Scrum ceremonies and contribute to a collaborative Agile engineering culture
Stay up to date with the rapidly evolving AI/ML ecosystem and proactively propose new tools, improvements, and approaches
Mentor junior team members and share AI engineering best practices
Must Have
3–5 years of experience in Software Engineering, with at least 1–2 years focused on AI / ML Engineering
Strong proficiency in Python
Experience with AI/ML and LLM frameworks such as LangChain, LangGraph, Hugging Face, PyTorch, or similar
Hands-on experience building RAG systems, including embeddings, vector stores, semantic search, and hybrid search strategies
Experience working with LLM APIs such as AWS Bedrock, OpenAI API, Anthropic API, or similar
Solid understanding of prompt engineering, fine-tuning techniques, and LLM evaluation methodologies
Hands-on experience with AWS services such as EC2, S3, Lambda, Aurora/RDS, Bedrock, SageMaker
Experience with Docker and Kubernetes
Familiarity with data pipeline tools such as Apache Airflow, Prefect, or similar
Experience developing backend services or APIs, ideally with FastAPI
Proficiency with Git and software engineering best practices
Experience working in a Scrum Agile environment
Strong problem-solving, analytical thinking, communication, and teamwork skills
Fluent English
Nice to Have
Experience with multi-agent architectures and protocols such as A2A or MCP
Familiarity with MLOps practices: model versioning, experiment tracking, MLflow, Weights & Biases, and CI/CD for ML
Experience with observability and evaluation platforms for LLMs such as Langfuse, Datadog LLM Observability, LangSmith
Knowledge of graph databases or knowledge graphs for enhanced retrieval
Experience with CI/CD pipelines using tools such as GitHub Actions
Familiarity with Infrastructure as Code, especially Terraform
Experience with code quality and security tools such as SonarCloud, Snyk
Experience in aviation, travel, or large-scale digital environments
Spanish language skills are a plus
Hybrid model - 2 days onsite per week
Why join this project?