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Senior Data Engineer – AI & Agentic Systems

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Onsite

Senior Data Engineer – AI & Agentic Systems

Virtual Connect Solutions

Senior Data Engineer – AI & Agentic Systems

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonJavaDatabricksMachine LearningAIScalaAWSApache AirflowTerraformAzure

13 days ago

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Important information


Contract type:

Permanent

Salary:

€50,000 – €80,000 / year

Location:

London, UK

Work mode:

Onsite

Published on:

13 October 2026

What they need


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

Skills: terraform,python,mlops

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