Applied AI Engineer

Principal Applied AI Engineer

Location: United Kingdom or Netherlands (Remote/Hybrid)

My client is an enterprise software company that is making a significant investment in AI-native products and building a team of Applied AI Engineers to help define the next generation of its platform.

This is a highly hands-on role focused on designing, building, deploying, and operating production AI systems. You'll own AI-powered product features end-to-end, working across application development, agent orchestration, retrieval systems, deployment, observability, and customer-facing implementation.

This is not a research role. We're looking for engineers who have shipped real AI products to real users and understand the challenges that come with operating them in production.

What You'll Do

• Build AI-powered product features from concept through production
• Design and deploy agentic systems, tool-calling workflows, and multi-step reasoning architectures
• Build and optimize RAG pipelines, retrieval systems, and knowledge architectures
• Develop evaluation frameworks and testing strategies for non-deterministic AI systems
• Work across the stack, including frontend, backend, infrastructure, and deployment
• Partner closely with product, engineering, and customers to deliver impactful AI capabilities
• Help establish best practices for production AI engineering across the organization

What We're Looking For

Production AI Experience

• Proven experience shipping LLM-powered products to production
• Experience operating AI systems at scale and managing real-world failure modes
• Strong understanding of model selection, prompting strategies, context management, and reliability

Agentic Systems & RAG

• Experience building agentic workflows and tool-calling systems
• Experience with frameworks such as LangGraph, CrewAI, AutoGen, or custom agent architectures
• Strong understanding of retrieval systems, embeddings, vector databases, hybrid search, and re-ranking
• Familiarity with GraphRAG is a plus

AI Evaluation & Observability

• Experience building evaluation frameworks for AI systems
• Familiarity with regression testing, LLM evaluation methodologies, and performance monitoring
• Experience with tools such as LangSmith, Langfuse, Braintrust, OpenTelemetry, or similar platforms

Engineering Fundamentals

• Strong Python development experience in production environments
• Experience with TypeScript, modern web frameworks, and API development
• Comfortable working with cloud infrastructure, containers, CI/CD pipelines, and Kubernetes
• Experience deploying and operating services in Azure environments is preferred

Ideal Background

We're particularly interested in engineers who have experience building customer-facing AI products, working closely with users, and owning systems from idea through production.

Experience in enterprise SaaS, industrial software, operations technology, maintenance platforms, or forward-deployed engineering environments is beneficial but not required.

What We're Not Looking For

• AI strategists without recent hands-on engineering experience
• Researchers without product or deployment experience
• Candidates whose experience is limited to demos, prototypes, hackathons, or internal chatbots
• Engineers who cannot clearly explain how they evaluate AI systems in production

If you're excited about building production AI products, working closely with customers, and helping shape an AI-native platform from the ground up, we'd love to hear from you.