Senior Data Engineer - AI & Agentic Systems
Virtual Connect Solutions
London, UK
21 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
Β£50,000.0 - Β£80,000.0
Working hours
Regular working hours
Languages
English
Job source
Tech stack
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
+19 more
SQL Databases
Cloud Platform System
Feature Engineering
LangChain
Retrieval-Augmented Generation
Prompt Engineering
Apache Spark
Multi-Cloud
Generative AI
Langfuse β LLM Observability and Analytics Platform
Agentic-AI
LangSmith
Information Technology
Dask
Data Management
Machine Learning Operations
Terraform
Data Pipelines
Databricks
Job 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.
Requirements
- 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
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