> Markdown version of [/jobs/ext/4610769-ai-engineer](https://www.wearedevelopers.com/jobs/ext/4610769-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).

---

# AI Engineer

- **Company:** Digital Waffle
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £80,000.0 - £110,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Structures, Monitoring of Systems, Machine Learning, Systems Architecture, Cloud Platform System, Generative AI, HybridCloud, Kubernetes, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** November 7, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5956109813

## About the Role

Required

 * 5+ years of experience in machine learning, data science, or AI system design.
 * Proven track record of deploying ML models or LLM-based applications to production.
 * Strong programming fundamentals, including data structures and algorithms.
 * Hands-on experience with transformers, embeddings, and vector databases.
 * Experience running AI workloads on offline or on-premise platforms (non-cloud environments).
 * Solid understanding of data pipelines, APIs, and scalable system architecture.

Preferred

 * Experience leading small teams or mentoring other engineers.
 * Familiarity with MLOps tools and best practices.
 * Background in integrating AI solutions into enterprise products.
 * Awareness of privacy, bias mitigation, and model explainability techniques.

## Description

As our first senior AI hire, you'll take ownership of designing and building the foundation of our AI ecosystem. You'll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you'll play a key role in recruiting and mentoring two mid-level AI engineers who will join your team., * Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud).

 * Design MLOps workflows for training, deploying, and monitoring models.
 * Integrate and manage containerized AI engines (Docker/Kubernetes).
 * Establish best practices for model versioning, data pipelines, and reproducibility.
 * Collaborate with ML and NLP researchers to optimize infrastructure for experimentation.
 * Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure.
 * Lead future recruitment and mentoring of additional AI engineers.