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# Senior Data Engineer - AI & Agentic Systems

- **Company:** Virtual Connect Solutions
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £50,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, User Authentication, Microsoft Azure, Continuous Integration, Information Engineering, Data Security, Python (Programming Language), Machine Learning, Role-Based Access Control, SQL Databases, Cloud Platform System, Feature Engineering, LangChain, Retrieval-Augmented Generation, Prompt Engineering, Apache Spark, Multi-Cloud, Generative AI, Langfuse — LLM Observability and Analytics Platform, Agentic-AI, LangSmith, Information Technology, Dask, Data Management, Machine Learning Operations, Terraform, Data Pipelines, Databricks
- **Published:** October 13, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5926648251

## About the Role

* A degree in Computer Science or Engineering, or equivalent experience
 * 5+ years in data engineering, including leading technical workstreams and mentoring engineers
 * Expert-level Python and SQL, plus comfort with Scala or Java when client systems need them
 * Hands-on experience building Agentic AI, GenAI, ML and BI systems in production with frameworks such as Spark, Databricks, LangChain, Dask, Airflow, Dagster or Kedro
 * Practical knowledge of RAG, embeddings, vector databases and prompt and context engineering
 * Strong MLOps/LLMOps skills:
 + CI/CD for data workflows
 + Automated agent evaluation (LangSmith, Langfuse, Opik)
 + Infrastructure as code (Terraform)
 * Experience on at least one major cloud (AWS, Azure or GCP); multi-cloud is a plus
 * Proven experience with data security and governance (PII/PHI, authentication, RBAC)
 * The ability to own workstreams on your own, with excellent time management
 * Clear, confident written and verbal communication in English

## Description

* 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.