Senior Python Backend Engineer (AI/LLMs) - Permanent Position
Posted 2 days 5 hours ago by Nicoll Curtin Technology
Senior Python Backend Engineer (AI/LLMs)
Remote (United Kingdom) | Permanent | Flexible compensation (DOE), performance based bonus + equity
We're working with a well-established, tech-led business that is building a new AI product focused on handling real-world tasks, workflows and decision-making.
This is a small, high-calibre team building systems where AI capability is translated into reliable, structured product behaviour, with a strong emphasis on execution and consistency in real usage.
The product focuses on:
- Long-running workflows
- Persistent context
- Multi-step task execution
- Integration with external systems
The core challenge is designing systems that can apply model capability in a structured and reliable way, even when behaviour is non-deterministic.
The Role
This role sits in the Back End layer that connects models to the product.
The focus is on designing and operating systems that enable:
- AI workflows to run end-to-end
- APIs to serve AI features consistently
- Systems to perform reliably under real usage conditions
You'll be working on:
- Inference pipelines and orchestration layers
- Backend services for AI-driven workflows
- Performance considerations such as latency, throughput, batching and caching
- Monitoring, logging and production reliability
What They Care About
The hiring bar is centred around real production experience:
- Whether you have owned Back End systems end-to-end in production
- Your experience working with AI systems beyond simple integration
- Your exposure to practical challenges such as:
- latency and throughput optimisation
- monitoring and observability
- debugging and incident handling
- scaling systems in production environments
Tech Environment
- Python (primary Back End language)
- Node.js
- SQL/NoSQL databases
- LLM ecosystem (OpenAI, Anthropic, etc.)
- Docker and Kubernetes
- AWS, Azure or GCP is fine
Compensation
Flexible compensation assessed based on the candidates impact, ownership and ability to deliver in production environments, alongside equity and performance based bonus.