Senior Ai Engineer

As you contemplate your future, you might be asking yourself, ” What’s the next step?’’ Start your journey with usWe’re seeking an experienced AI Engineer to join our Data Science team in Barcelona (Hybrid) to build the applications, and agents that put generative AI in front of over 20 million customers. You will be working with the DS, ML Engineers, and SWE as a hands-on engineering role designing and building AI-powered products and services while making sure they’re reliable, evaluated and safe to ship. If you’re ready to soar, we’re ready to take you there.
Why eDreams ODIGEOJoin the world’s leading travel subscription platform…
- We pioneered Prime, the first and world’s leading travel subscription programme since launching in 2017.
- Millions of Prime members every year across multiple markets.
- 5 brands: eDreams, GO Voyages, Opodo, Travellink, and the metasearch engine Liligo
- This entire Prime experience is powered by a proprietary, industry-leading AI platform that delivers a smarter, hyper-personalised service and comprehensive travel experience globally to its members.
- Diversity is our strength that’s why our eDOers are coming from different nationalities from all continents – 99% permanent contractsPrime members are subscribed to global travel, gaining access to a comprehensive multi-product offering for all their travel needs—including hotels, rail, flights, dynamic packages and car rental, among others— compounded by industry-leading flexibility features and exclusive, member-only benefits.
What you will do:The Role’s

Key Responsibilities
As an eDOer, you will have clear objectives, great challenges and a clear overview of how your work contributes to the global company project and its customers. As a Senior AI Engineer in the Data Science team you will be in charge of:
- Design, build and ship LLM-powered features (chatbots, agents, RAG-based search, etc) in close collaboration with Data Science, ML Engineering, IT, and Product.
- Design LLM applications ranging from pragmatic efficient single-model calls to sophisticated autonomous agents. Use the right frameworks (e.
G. LangGraph, Google ADK) to deliver the required agent architecture, manage the underlying LLMs and provide the needed tools and APIs.
- Own context engineering as a first-class engineering discipline; treat like code – versioning, testing and evaluating – all model context and configuration.
- Work with ML Engineering to deploy AI applications on our cloud platform (GCP), reusing existing MLOps infrastructure where it fits and flagging gaps where it doesn’t.
- Evaluate, monitor and observe AI features in production and build controls to prevent and minimize model failures and security risks; track model and data drift. Trace model calls, tool usage and agent decisions. Measure costs, latency and build failure safety nets, guardrails and apply security engineering.
- Stay current on the fast-moving GenAI landscape and bring back what’s worth adopting; share knowledge and best practices across the organisation.
What you need to succeed:Good to haveBring your unique perspective, speak up, and offer disruptive solutions. You’ll have the opportunity to learn and grow while making a real impact on our team. Here’s what you need to succeed:
- Degree in a quantitative or engineering field (Computer Science, Engineering, Mathematics, or related); equivalent hands‑on experience also welcome.
- Demonstrated experience as an AI Engineer, Ideally, 5+ years as a Data Scientist or Software Engineer.
- An excellent production software engineer that understands AI model behavior. Strong Python skills, with solid software engineering fundamentals: APIs, orchestration, observability, measurement, runtime constraints, reliability, production debugging, testing, version control, code review, CI/CD, etc.
- Experience building and orchestrating LLM agents and tool use, and a working understanding of prompt engineering and context‑window management.
- Experience with LLM evaluation methods (LLM-as-judge, human review, model based evals, task‑specific datasets…) and production feedback loops plus an instinct for measuring before claiming something works.
- Experience with cloud platforms (GCP preferred) and shipping APIs or services into production.
- Comfortable working with ambiguity and fast‑changing tooling; pragmatic about pickingthe right level of complexity for the problem.
- Written and oral communication skills in English.
Preferred Qualifications
- Experience fine‑tuning or distilling open‑weights models; exposure to MLOps/LLMOps tooling (MLflow, Vertex AI, Kubeflow); background in NLP.
What’s in it for you?The best talent deserves the best benefitsAt eDO, we want you to be a part of our success story and great culture.
Here’s

what we offer
- A rewarding Compensation package Prime Plus membership, competitive salary and benefits package, including flexible benefits, performance‑based bonuses, birthday day off, discounts and partnerships, relocation suppo