> Markdown version of [/jobs/ext/3332296-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3332296-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior AI Engineer

- **Company:** Currys PLC
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £47,551.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Cloud Computing, Information Engineering, DevOps, Python (Programming Language), SQL Databases, Data Processing, Snowflake, Cloudformation, Event Driven Architecture, Information Technology, Integration Frameworks, Video Streaming, Terraform, Data Pipelines, Databricks
- **Published:** September 29, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5902951202

## About the Role

* Strong experience building production-grade data pipelines at scale that handle real business impact
 * Confidence with Python and SQL, and hands-on use of data processing frameworks in live environments
 * Experience with cloud platforms like Azure or GCP and containerisation technologies
 * Knowledge of streaming technologies and event-driven architectures that keep data flowing
 * A practical approach to infrastructure as code using tools like Terraform or CloudFormation
 * Sharp troubleshooting skills that get to the root of problems and fix them for good
 * Experience with platforms like Databricks or Snowflake, or similar data tools
 * Interest or experience in building Al-powered solutions - hands-on with Databricks Agent Bricks beneficial
 * Degree in Computer Science, Engineering, or equivalent hands-on experience
 * Cloud certifications highly desirable
 * DevOps, data engineering, or Al engineering certifications beneficial

## Description

* Build and maintain data pipelines that process billions of events daily across batch and streaming systems
 * Develop Al-powered solutions including intelligent agents using Databricks Agent Bricks to improve
 * Productivity
 * Setup infrastructure as code for data and Al platforms, keeping everything scalable and reproducible
 * Create monitoring and alerting systems that protect data quality, model performance and pipeline
 * Reliability
 * Optimise data processing jobs to improve performance and cut costs
 * Partner with product and domain teams to deliver new data features and agent-driven tools
 * Build and manage CI/CD pipelines for data and Al applications
 * Troubleshoot production issues and apply permanent fixes to stop problems recurring
 * Contribute to shared engineering standards and best practices across the team