Job Specifications
AI Prompt Engineer, 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.
Remote Working Some remote working
Country United Kingdom
Location London and home
Reference swx1616915prompt
Start Date Jan 26
Duration 6-12 months initial, outside IR35
Rate market rates, outside IR35
Visa Requirement Applicants must be eligible to work in the specified location