AI Prompt Engineer (technical engineering)

Job ID: 10954Location: London, England, GBType: AnySalary: USD market per yearPosted: 2025-11-27AI Prompt Engineer, Technically Sharp & Systems-MindedYou’ll design and optimize prompts, architect LLM-powered systems and deploy scalable GenAI workflows that connect people and intelligent systems in new, high-impact ways.THE ROLEPrompting & Reasoning SystemsDesign, test and optimize prompts for leading frontier models (GPT-4/5, Claude 3.x, Gemini 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek).Apply advanced prompting strategies: Chain-of-Thought, ReAct, Tree-of-Thoughts, Graph-of-Thoughts, Program-of-Thoughts, self-reflection loops, debate prompting and multi-agent orchestration (AutoGen/CrewAI).Build agentic workflows with tool calling, memory systems, retrieval pipelines and structured reasoning.GenAI Application EngineeringIntegrate LLMs into applications using LangChain, LlamaIndex, Haystack, AutoGen and OpenAI’s Assistant API patterns.Build high-performance RAG pipelines using: hybrid search, reranking, embedding optimization, chunking strategies and evaluation harnesses.Develop APIs, microservices and serverless workflows for scalable deployment.ML/LLM EngineeringWork with AI+ML pipelines through Azure ML, AWS SageMaker, Vertex AI, Databricks, or Modal/Fly.io for lightweight LLM deployment.Utilize vector databases (Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores.Use AI-powered dev tools (GitHub Copilot, Cursor, Codeium, Aider, Windsurf) to accelerate iteration.Implement LLMOps/PromptOps using: Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize PhoenixBenchmark and evaluate LLM systems using Ragas, DeepEval and structured evaluation suites.Deployment & InfrastructureContainerize and deploy workloads with Docker, Kubernetes, KNative and managed inference endpoints.Optimize model performance with quantization, distillation, caching, batching and routing strategies.EXPERIENCEStrong Python skills, with experience using Transformers, LangChain, LlamaIndex and the broader GenAI ecosystem.Deep understanding of LLM behavior, prompt optimization, embeddings, retrieval and data preparation workflows.Experience with vector DBs (FAISS, Pinecone, Milvus, Weaviate, ChromaDB).Hands-on knowledge of Linux, Bash/Powershell, containers and cloud environments.Strong communication skills, creativity and a systems-thinking mindset.Curiosity, adaptability and a drive to stay ahead of rapid advancements in GenAI.BENEFICIALExperience with PromptOps & LLM Observability tools (PromptLayer, LangFuse, Humanloop, Helicone, LangSmith).Understanding of Responsible AI, model safety, bias mitigation, evaluation frameworks and governance.Background in Computer Science, AI/ML, Engineering, or related fields.Experience deploying or fine-tuning open-source LLMs.TECH STACKLLMs: GPT-4/5, Claude 3.x, Gemini 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeekFrameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAITools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, HumanloopCloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, ModalInfra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, RedisStaffworx are a UK based Talent & Recruiting Partner, supporting Digital Commerce, Software and Value Add Consulting sectors across the UK & EMEA.