Permanent position: Senior Python Backend Engineer (AI Systems)
Why This Role Stands Out
This remote Senior Python Backend Engineer role offers a unique opportunity to build and scale cutting-edge AI systems, turning model capabilities into real-world product experiences. You'll thrive here if you enjoy tackling complex backend challenges, optimizing for reliability and performance, and contributing to an innovative AI-first company with flexible compensation and potential for significant impact. Apply now to be at the forefront of autonomous AI technology!
Quick Overview
Job Description
Senior Backend Engineer (AI Systems)
Remote (United Kingdom) | Permanent | Flexible compensation (DOE), performance bonus + equity
We're working with a well-funded, AI-first technology business building systems that go beyond traditional chatbot experiences and execute real-world tasks autonomously.
The team is focused on creating AI product systems that can reliably complete meaningful work for users, handling long-running workflows, maintaining context over time, interacting with external tools, and operating consistently in production environments.
This is not a pure model development role. The challenge is turning model capability into reliable product behaviour, ensuring AI systems can perform correctly when interacting with real users and live services at scale.
The Opportunity
This role sits between models and users, owning the systems that power AI behaviour in production.
You'll be responsible for building and operating the infrastructure and workflows that allow AI features to execute end-to-end, with a strong focus on reliability, observability, latency, and user experience.
Areas of responsibility include:
- Building production Back End systems that serve AI-powered product features
- Designing retrieval, inference, and orchestration workflows
- Developing reliable multi-step AI workflows and agent systems
- Integrating models with external tools, services, and APIs
- Monitoring, evaluating, and improving AI behaviour in production
- Optimising latency, throughput, caching, batching, and streaming
- Debugging failures across distributed systems and AI workflows
- Building observable systems with robust monitoring and incident response capabilities
What They're Looking For
The team is particularly interested in engineers who have experience operating AI systems in production rather than simply integrating model APIs.
Examples of relevant experience include:
- Retrieval-Augmented Generation (RAG)
- Agentic or multi-step AI workflows
- Tool calling and workflow orchestration
- LLM-based applications used by real users
- Vector databases and semantic search
- AI evaluation and monitoring frameworks
- Production observability and reliability engineering
- Distributed systems and high-throughput services
- End-to-end ownership of Back End systems in production
Technical Environment
- Python
- Node.js
- SQL/NoSQL
- OpenAI, Anthropic and open-source LLMs
- Vector databases and retrieval systems
- DevOps - Docker/Kubernetes
- AWS, Azure or GCP
Compensation
Compensation is intentionally flexible and assessed based on experience, ownership, and production impact.
The package includes:
- Competitive base salary
- Performance-based bonus
- Equity
- Fully remote working
- Private healthcare
- Pension contribution
- Dental/Vision/Life insurance
- Generous paid holiday allowance
Skills
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