This position is at T-Systems

The selection process will be entirely managed by T-Systems.

--

Job Description We are looking for Senior AI Engineers to participate in the construction and industrialization of business solutions based on generative artificial intelligence, RAG, intelligent agents, automation, integration with corporate systems and cloud services. The selected individuals will be part of multidisciplinary technical teams and will participate in the presente implementation of AI components, data pipelines, backend services, integration with APIs, agents, prompts, tools, automations and evaluation mechanisms. A senior, practical profile with solid experience in software development and applied knowledge of generative AI is required . We will evaluate applications from all over the country, especially Seville, Granada, Tarragona, Madrid, Valencia... Cities where we have work centers.

Responsibilities

- Design, develop and integrate generative AI components into business solutions.
- Implement services, APIs, connectors and backend components to expose AI capabilities.
- Build pipelines for ingesting, normalizing, processing and preparing structured and unstructured data.
- Implement RAG solutions based on documentation, knowledge bases, historical data, documentary repositories and corporate sources.
- Work with LLMs, embeddings, vector databases, semantic search engines and agent frameworks.
- Design and implement prompts, tools, workflows, agents and structured generation mechanisms.
- Integrate AI solutions with APIs, internal services, external services, corporate tools and legacy systems.




- Participate in the development and termination of services using automatic code generation tools.
- Implement automations using APIs, scripts, runbooks, workflows, or RPA when applicable.
- Participate in the definition and implementation of quality metrics, evaluation of responses, technical tests and validation of results.
- Collaborate with architects, cloud teams, development, operation, security teams and functional stakeholders.
- Participate in the continuous improvement of internal AI tools, accelerators, prompts, agents, pipelines and building blocks.
- Keep up to date with the latest advances in applied AI, software development, RAG, agents, automation and cloud.

Requirements

- Minimum experience of 3 years in software development and participation in the delivery of technological projects.
- Knowledge of ITSM, CRM, ERP tools, corporate portals, document repositories or legacy systems.
- Practical experience in generative AI solutions, LLMs, RAG, agents or intelligent automation.
- Knowledge in LLMs, embeddings, vector databases, prompting, semantic retrieval and response evaluation.
- Experience in backend development, APIs and system integration.
- Strong development knowledge in Java, .NET, Python, Javascript/TypeScript or other business stacks.
- Proficiency or good knowledge of JavaScript frameworks:



Angular, React, Vue or others.
- Experience with GitHub, GitLab, Azure DevOps, or other version control and CI/CD tools.
- Knowledge of SDLC, DevOps, testing, observability, quality gates and good software engineering practices.
- Experience integrating solutions with APIs, internal services, external services and corporate systems.
- Experience in classic, agile or hybrid project management methodologies.
- Experience in participating in the execution of technological projects.
- Degree in Computer Science, Telecommunications, Engineering or similar. MECES 2 or equivalent demonstrable experience is recommended.

Valuable requirements

- Python applied to AI, automation, data or integration.
- Experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI or equivalent frameworks.
- Experience with Azure AI, Azure OpenAI, Azure AI Search, OpenAI API, Anthropic, Vertex AI, open-source models, or similar platforms.
- Experience with vector bases: Qdrant, Weaviate, Milvus, Chroma, Pinecone, OpenSearch, Elasticsearch or others.
- Experience in NLP, classification, entity extraction, clustering, semantic matching or text mining.
- Experience in automation using APIs, scripts, RPA, workflows, runbooks or orchestration tools.
- Experience in observability: logs, metrics, traces, health checks, dashboards or AIOps.
- Knowledge in Platform Engineering, building blocks tooling, compliance tools, SBOM, quality gates and technical governance.
- Certifications or training in generative AI, prompt engineering, cloud, DevOps or software development.

📌 Senior AI Engineer (Bilbao)
🏢 T-Systems
📍 Bilbao