kadence
Artificial Intelligence Engineer
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Applied AI Engineer
Location: UK or Netherlands | Hybrid or Remote
Compensation: Highly competitive base + package
We’re partnering with a leading B2B software company that is making a significant investment in AI-native product development. They’re building a new generation of intelligent, agentic product experiences designed to solve complex, real-world problems for customers operating in demanding environments.
We’re looking for experienced Applied AI Engineers who can take AI-powered product features from an ambiguous problem through to reliable production.
This isn’t a research role, and it isn’t about building demos or experimenting with the latest framework. You’ll work as part of a product squad, partnering with engineers, product leaders and customers to understand problems, make thoughtful architectural decisions, and ship AI systems that people actually use.
What You’ll Do
You’ll own meaningful parts of AI-native product development end-to-end, including:
- Designing and shipping production-grade LLM-powered product features
- Building agentic systems, including tool calling, orchestration, multi-step workflows, memory, validation and human-in-the-loop patterns
- Designing and operating RAG and retrieval systems, including chunking, embeddings, hybrid search, re-ranking and provenance
- Exploring GraphRAG and knowledge-driven retrieval for complex, interconnected data
- Building evaluation strategies for non-deterministic AI systems, including regression testing, trajectory evaluation and quality monitoring
- Making architectural decisions around model selection, prompting, latency, reliability, cost and scalability
- Working across the stack when needed—from backend services and APIs through to product interfaces and deployment
- Deploying and operating your own work in production, with appropriate observability and monitoring
- Working directly with customers and product teams to understand workflows, validate assumptions and ensure you’re solving the right problem
- Helping raise the AI engineering capability of the wider product and engineering organization
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What We’re Looking For
We’re less interested in whether you’ve used a specific framework and more interested in how you think as an engineer.
You’ll likely be a strong fit if you:
- Have recently shipped LLM/GenAI-powered features into production for real users
- Have strong software engineering fundamentals and are comfortable working in Python
- Can reason about architecture and clearly explain the trade-offs behind your decisions
- Have hands-on experience with RAG, agents, tool calling, orchestration and evaluation
- Understand what changes when an AI system moves from a prototype to production—including hallucinations, latency, failure modes, observability, cost and reliability
- Are comfortable working across backend engineering, APIs, deployment infrastructure and the broader product stack
- Think about the customer and product problem before reaching for a technical solution
- Can explain complex AI concepts simply, without relying on jargon
- Enjoy ambiguity and 0→1 product development
- Take ownership from initial problem through to production
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Experience with technologies such as React/TypeScript, FastAPI, Azure, Kubernetes, Terraform, vector databases and AI observability platforms is useful, but specific tooling is not the deciding factor.
What Will Make You Stand Out
We’d particularly like to hear from engineers who have:
- Built and maintained multiple production AI systems
- Worked in a forward-deployed, customer-facing or highly product-oriented engineering role
- Designed evaluation frameworks for LLM or agentic systems
- Made real architectural trade-offs across models, retrieval approaches, latency, quality and cost
- Worked closely with end users to understand workflows and translate messy problems into effective products
- Experience building software for complex B2B, enterprise or operational environments
The Opportunity
This is an opportunity to join a well-established software business at an important point in its AI journey.
Rather than adding AI around the edges of an existing product, the team is investing in AI-native product experiences and giving engineers meaningful ownership over how they are designed and built.
You’ll work closely with senior technical leadership while joining a small group of engineers tasked with taking these products from concept to production.
If you’re an engineer who likes asking “What problem are we actually trying to solve?” before deciding what to build and you have the technical depth to then ship it, we’d love to speak with you.
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