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You will design, develop, and integrate LLM-powered features and backend components while managing the full AI development lifecycle. This includes refining prompts, implementing RAG workflows, and monitoring model performance in production environments.
Our client is looking for an AI LLM Engineer to help build and improve AI-powered products. In this role, you will develop and integrate large language model (LLM) solutions, turning product and user needs into reliable, high-quality features.
You will work with engineering and product colleagues in a remote, international environment, contributing across the LLM development lifecycle—from experimentation and evaluation to deployment and ongoing improvement.
Design, develop and integrate LLM-powered features and services
Build and maintain reliable backend components and APIs for AI applications
Develop and refine prompts, workflows and model configurations to improve response quality
Explore techniques such as retrieval-augmented generation (RAG), embeddings and tool use where appropriate
Evaluate model outputs for quality, accuracy, consistency and relevance using appropriate tests and metrics
Monitor AI features in production and investigate performance or reliability issues
Collaborate with product, engineering and other stakeholders to define requirements and deliver solutions
Contribute to decisions about model selection, integration approaches and system architecture
Apply responsible AI practices, considering privacy, security, safety and potential model limitations
Document technical decisions, workflows and evaluation results
Keep up to date with developments in LLMs and related AI technologies, identifying opportunities to improve products
Professional experience in software engineering, machine learning or a related technical role
Experience building applications or services that use large language models
Strong programming skills in Python or another relevant language
Understanding of LLM APIs, prompt design and the strengths and limitations of generative AI models
Experience with backend development, APIs and integrating external services
Familiarity with evaluation methods for AI systems, including testing model outputs and tracking quality
Understanding of data handling, privacy and security considerations when working with AI systems
Experience with RAG, vector databases, embeddings or AI orchestration frameworks is an advantage
Familiarity with cloud platforms, containers, CI/CD or production monitoring is an advantage
Strong analytical and problem-solving skills, with attention to reliability and maintainability
Clear communication skills and the ability to collaborate effectively in a remote team
Comfortable working independently, managing priorities and adapting to a fast-changing technical landscape
Ability to work remotely within the EMEA region
Remote opportunity for candidates based in the EMEA region
Opportunity to build and improve products powered by large language models
Collaborative work with colleagues across product and engineering
Scope to contribute to technical decisions and the development of AI solutions
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