Burns Sheehan
Senior Backend AI Engineer
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Senior Backend AI Engineer – Python | LLM Workflows
📍 Hybrid, London (1 day/week)
💵 £90,000-120,000 + equity
💻 Python, LLM workflows, AI orchestration, LangFuse
📈 AI SaaS platform – live with major enterprise clients
⚙️ Small, high-calibre engineering team – real ownership, AI-native product building
We're partnered with a fast-growing AI startup on a mission to help large organisations harness AI at scale. Their platform is already live with major enterprise clients across professional services, government and tech – and they're scaling quickly off the back of a recent Seed round backed by some of the UK's top investors.
They’re now looking to hire a Senior Backend AI Engineer. This is a backend-leaning engineer with hands-on experience building AI-powered products and chaining LLM-driven processes into production workflows. They want someone who understands how to turn LLM capability into reliable internal tooling, user-facing product features, and repeatable AI workflows.
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The engineering team is small, sharp, and highly product-focused. Engineers work with real ownership and move quickly, with the chance to shape how AI systems are designed and deployed across the platform. The environment is genuinely AI-native, with strong internal adoption of AI tooling and a high bar for practical fluency.
You’ll be joining at an exciting point in the company’s growth: the product is already proven in market, but there’s still lots of room to influence architecture, workflow design, and how AI capabilities are embedded into the product over time.
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Ideal profile:
- Strong backend engineering background, ideally using Python
- Experience building AI products or AI-powered internal tools in production
- Hands-on experience creating LLM workflows or chaining multi-step AI processes end-to-end
- Comfortable designing reliable backend systems around AI use cases, not just basic API integrations
- Experience with workflow/orchestration tooling (LangFuse exposure is a strong bonus)
- Also open to engineers who’ve built custom AI pipelines using other workflow engines or orchestration patterns
- Able to work in a product-minded way, translating AI capability into practical features and business value
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