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# Ai Engineer

- **Company:** Titan OS
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, BigQuery, Code Review, Content Analysis, Github, Python (Programming Language), PostgreSQL, Machine Learning, Node.Js, Recommender Systems, Tensorflow, Prometheus, Ruby, SQL Databases, Pytorch, Large Language Models, Grafana, Apache Spark, Deep Learning, Backend, Pandas, AI Platforms, Integration Tests, Information Technology, Apache Flink, Apache Kafka, Machine Learning Operations, Restful APIs, Stream Processing, Software Version Control, Data Pipelines, Docker, Smart Tv
- **Published:** August 26, 2026
- **Apply:** https://www.buscojobs.com.es/ai-engineer-en-barcelona-ID-368831548

## About the Role

Requirements What makes you a great fit: 2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions.
Bachelor's or Master's program in Computer Science, Data Science, Machine Learning, or a related field.
Solid grasp of probability, statistics, linear algebra, and algorithms.
Exposure to LLM-powered agents, familiarity with RAG pipelines, as well as with tool/function calling, multi-step planning and orchestration.
Proficiency in Python; familiarity with at least one ML/RL or deep-learning framework (PyTorch, TensorFlow, JAX).
Experience with SQL (BigQuery, PostgreSQL) and pandas / Spark.
Recommender Systems Exposure API Know-How: Understanding of REST services and how models are surfaced as endpoints.
Testing & Documentation: Awareness of unit/integration testing for data pipelines and eagerness to learn experiment-driven development.
Soft Skills: Clear communicator who thrives in a fast-paced, collaborative environment.
Desirable skills: Familiarity with real-time stream processing (Kafka, Flink) Exposure to AWS/GCP AI services Interest in LLM-based recommendation, embeddings, or content understanding.
Basic knowledge of observability stacks (Prometheus, Grafana) Comfort with an additional backend language (Go, Node.Js, or Ruby) for service integration.

## Description

Is this you?Titan Operating System S.L. (Titan OS), the Barcelona-based technology, entertainment, and advertising company, is looking for you!At TitanOS, we live by three core values: Make things happen - We take ownership, move fast, and deliver impact.No ego - We collaborate with respect and humility to reach shared goals.Show genuine passion - We love what we do and never stop learning.Culture and environment are at the heart of our ethos.If the above resonates with you, keep reading because we believe you could be a perfect addition to our incredible team!Role overview: As an AI & Content-Recommendation Engineer , you'll work with our Machine-Learning and Backend teams to design, train, and deploy the models and data pipelines that decide "what to watch next" on our Smart TV platform.You'll gain hands-on experience across the full ML lifecycle - from exploratory data analysis through online A/B testing - while shipping features used by millions of viewers worldwide.Key responsibilities Design, build and deploy LLM-powered agents that improve recommendation and information-retrieval experiences.Prototype and train ranking/recommendation models from large-scale interaction logs.Design offline metrics and analyze results.Help set up or monitor online A/B tests; turn findings into iteration plans.Expose recommendation APIs and integrate them with our existing Go / Ruby services.Contribute to CI/CD pipelines for data & model versioning (GitHub Actions, Docker).Code Reviews & Collaboration: Participate in peer reviews; give and receive constructive feedback.Work closely with product owners and teammates to prioritize and scope tasks.Follow Agile Processes: Adhere to sprint ceremonies, ticketing workflows, and documentation practices.Monitor & Measure: Assist in establishing basic SLAs and KPIs for service performance; learn to track and report on these metrics.Requirements What makes you a great fit: 2-3 years of experience in AI Engineering, with significant recent experience designing and deploying Gen AI and LLM-based solutions.Bachelor's or Master's program in Computer Science, Data Science, Machine Learning, or a related field.Solid grasp of probability, statistics, linear algebra, and algorithms.Exposure to LLM-powered agents, familiarity with RAG pipelines, as well as with tool/function calling, multi-step planning and orchestration.Proficiency in Python; familiarity with at least one ML/RL or deep-learning framework (PyTorch, TensorFlow, JAX).Experience with SQL (BigQuery, PostgreSQL) and pandas / Spark.Recommender Systems Exposure API Know-How: Understanding of REST services and how models are surfaced as endpoints.Testing & Documentation: Awareness of unit/integration testing for data pipelines and eagerness to learn experiment-driven development.Soft Skills: Clear communicator who thrives in a fast-paced, collaborative environment.Desirable skills: Familiarity with real-time stream processing (Kafka, Flink) Exposure to AWS/GCP AI services Interest in LLM-based recommendation, embeddings, or content understanding.Basic knowledge of observability stacks (Prometheus, Grafana) Comfort with an additional backend language (Go, Node.Js, or Ruby) for service integration.Benefits Reasons


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