AI Prompt Engineering Consultant

AI Prompt Engineering Consultant, Technically Sharp & Systems-Minded Deesign and optimize prompts, architect LLM-powered systems and deploy scalable GenAI workflows that connect people and intelligent systems in new, high-impact ways. THE ROLE Prompting & Reasoning Systems • Design, 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 Engineering • Integrate 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 Engineering • Work 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 Phoenix • Benchmark and evaluate LLM systems using Ragas, DeepEval and structured evaluation suites. Deployment & Infrastructure • Containerize and deploy workloads with Docker, Kubernetes, KNative and managed inference endpoints. • Optimize model performance with quantization, distillation, caching, batching and routing strategies. EXPERIENCE • Strong Python skills, with experience using Transformers, LangChain, LlamaIndex and the broader GenAI ecosystem and prompt engineering experience. • 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. BENEFICIAL • Experience 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 STACK LLMs: GPT-4/5, Claude 3.x, Gemini 2.x, Mistral Large, LLaMA 3, Cohere Command R+, DeepSeek Frameworks: LangChain, LlamaIndex, Haystack, AutoGen, CrewAI Tools: GitHub Copilot, Cursor, LangSmith, LangFuse, Weights & Biases, MLflow, Humanloop Cloud: Azure ML, AWS SageMaker, Google Vertex AI, Databricks, Modal Infra: Python, Docker, Kubernetes, SQL/NoSQL, PyTorch, FastAPI, Redis Staffworx are a UK based Talent & Recruiting Partner, supporting Digital Commerce, Software and Value Add Consulting sectors across the UK & EMEA.