Own technical workstreams. Design and deliver machine learning, Generative AI and agentic/autonomous AI systems from architecture through production.Architect scalable data platforms. Build robust batch and streaming pipelines that are tuned for modern AI workloads.Integrate GenAI and agentic frameworks into client solutions. This covers RAG pipelines, embeddings, vector databases, context construction, prompt design and output handling.Design MLOps/LLMOps architectures for model management, observability, automated evaluation and retraining.Lead feature engineering on complex workstreams so that data assets are reliable, reusable and ready for AI.Govern and secure data. Implement access controls, PII/PHI handling, authentication and RBAC across cloud environments.Make sound engineering trade-offs between quality, latency and cost. Apply evaluation, reliability and guardrail practices to AI features.Mentor and raise the bar. Coach junior engineers and drive software engineering best practices across the team.Partner with clients and stakeholders. Turn business problems into technical solutions and help build client capabilities.What You Will DoOwn technical workstreams. Design and deliver machine learning, Generative AI and agentic/autonomous AI systems from architecture through production.Architect scalable data platforms. Build robust batch and streaming pipelines that are tuned for modern AI workloads.Integrate GenAI and agentic frameworks into client solutions. This covers RAG pipelines, embeddings, vector databases, context construction, prompt design and output handling.Design MLOps/LLMOps architectures for model management, observability,



automated evaluation and retraining.Lead feature engineering on complex workstreams so that data assets are reliable, reusable and ready for AI.Govern and secure data. Implement access controls, PII/PHI handling, authentication and RBAC across cloud environments.Make sound engineering trade-offs between quality, latency and cost. Apply evaluation, reliability and guardrail practices to AI features.Mentor and raise the bar. Coach junior engineers and drive software engineering best practices across the team.Partner with clients and stakeholders. Turn business problems into technical solutions and help build client capabilities.Must haveA degree in Computer Science or Engineering, or equivalent experience5+ years in data engineering, including leading technical workstreams and mentoring engineersExpert-level Python and SQL, plus comfort with Scala or Java when client systems need themHands-on experience building Agentic AI, GenAI, ML and BI systems in production with frameworks such as Spark, Databricks, LangChain, Dask, Airflow, Dagster or KedroPractical knowledge of RAG, embeddings, vector databases and prompt and context engineeringStrong MLOps/LLMOps skills:CI/CD for data workflowsAutomated agent evaluation (LangSmith, Langfuse, Opik)Infrastructure as code (Terraform)Experience on at least one major cloud (AWS, Azure or GCP); multi-cloud is a plusProven experience with data security and governance (PII/PHI, authentication, RBAC)The ability to own workstreams on your own, with excellent time managementClear, confident written and verbal communication in EnglishSkills: python,mlops,terraform#J-18808-Ljbffr

📌 Senior Data Engineer – Ai & Agentic Systems (Madrid)
🏢 Virtual Connect Solutions
📍 Madrid