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Senior Data Engineer – AI & Agentic Systems

Virtual Connect Solutions
1 day ago
Full-time
On-site
United Kingdom
Data Engineer

What You Will Do

  • 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.

Must have

  • 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