> Markdown version of [/jobs/ext/4593184-software-engineer](https://www.wearedevelopers.com/jobs/ext/4593184-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** T-Systems Iberia - **Location:** Bilbao, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Cloud Computing, Databases, DevOps, Language Modeling, Data Processing, LangChain, Retrieval-Augmented Generation, Large Language Models, Generative AI, Backend, Agentic-AI, CrewAI, Nintex, Data Management, Machine Learning Operations, Restful APIs - **Published:** November 6, 2026 - **Apply:** https://www.adzuna.es/details/5954156896 ## About the Role Job Description We are looking for a Software Engineer specialized in Generative AI solutions and agentic architectures, with experience in the development of backend systems and data platforms in corporate environments. The profile will participate in the construction of agent-based use cases, integrating language models (LLMs), external tools and data sources, within a governed platform prepared for production. Responsibilities: Development of backend components for solutions based on AI and agents. Implementation of agentic flows (orchestration, tool calling, context management). Implementation of document processing and RAG pipelines. Collaboration with architects, data scientists and business teams. Requirements Essential Experience (+5 years) in developing backend solutions Approx. 3 years of experience in technological projects supported by AI or Data exploitation, and specifically, experience in creating solutions based on Generative AI and semantic data processing (RAG, ontologies, etc.), on Cloud or OnPrem Direct experience in LLMs, semantic databases and Genetic Frameworks such as Langraph, CrewAI, LangChain, n8n, etc. Familiarity with the use of DevOps, LLMops and MLOps technologies Conversation level English Valuable Experience in document processing (OCR, NLP) Knowledge of standards and procedures in the financial and banking sector. Technical certifications Knowledge in modern integration mechanisms such as Events, API Rest, MCP, etc. Additional Information What do we offer you? Environment and flexibility * International, dynamic and collaborative environment. * T-Social: social initiatives (sports, community, health,...). * Hybrid work model (teleworking/face-to-face). * Flexible schedule. * 4 weeks of teleworking per year. Professional Development * Tailor-made training: access to Coursera so you can learn what you want, when you want. * Weekly language classes (English, Spanish and German). * Global Mentoring Sessions and Experience, We are looking for a Software Engineer specialized in Generative AI solutions and agentic architectures with extensive backend development experience, expertise in AI and data platforms, and strong knowledge of language models and agent-based systems in corporate environments. Must Have Skills * 5+ years of experience in developing backend solutions * Approximately 3 years of experience in technological projects supported by AI or Data exploitation * Experience in creating solutions based on Generative AI and semantic data processing (RAG, ontologies, etc.) on Cloud or OnPrem * Direct experience with LLMs (Large Language Models) * Direct experience with semantic databases * Direct experience with Generative AI Frameworks such as Langraph, CrewAI, LangChain, n8n, etc. * Familiarity with DevOps technologies * Familiarity with LLMops technologies * Familiarity with MLOps technologies * Conversational level English Nice to Have Skills * Experience in document processing (OCR, NLP) * Knowledge of standards and procedures in the financial and banking sector * Technical certifications * Knowledge in modern integration mechanisms such as Events, API Rest, MCP, etc. ## Description * Development of backend components for solutions based on AI and agents * Implementation of agentic flows (orchestration, tool calling, context management) * Implementation of document processing and RAG pipelines * Collaboration with architects, data scientists and business teams