AI Prompt Engineer

Highnic; City of London; On-site; GBP 30,000 - 40,000; Part time

Job summary

A technology firm in the UK is seeking an AI Prompt Engineer with strong Python skills to design prompts and deploy AI systems. This entry-level contract role involves integrating LLMs into applications and optimizing workflows. Ideal candidates will have knowledge of prompt optimization and experience with tools like Transformers and LangChain.

Qualifications

• Experience using Transformers, LangChain, LlamaIndex in GenAI.
• Knowledge of prompt optimization and embeddings.
• Experience deploying or fine-tuning open-source LLMs.

Responsibilities

• Design and optimize prompts for leading frontier models.
• Integrate LLMs into applications using various APIs.
• Containerize and deploy workloads effectively.

Skills

Strong Python skills

Deep understanding of LLM behavior

Experience with vector DBs

Hands-on knowledge of Linux

Strong communication skills

Curiosity and adaptability

Education

Background in Computer Science, AI/ML, Engineering, or related fields

Tools

Transformers

LangChain

Docker

Kubernetes

Job description

AI Prompt Engineer Technically Sharp & Systems-Minded

Youll design and optimize prompts, architect LLM-powered systems and deploy scalable GenAI workflows that connect people and intelligent systems in new, high-impact ways.

What Youll Do

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).
• Buildagentic workflowswith tool calling, memory systems, retrieval pipelines and structured reasoning.

GenAI Application Engineering

• Integrate LLMs into applications usingLangChain,LlamaIndex,Haystack,AutoGen and OpenAIs 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 throughAzure ML,AWS SageMaker,Vertex AI,Databricks, orModal / Fly.iofor lightweight LLM deployment.
• Utilizevector databases(Pinecone, Weaviate, Milvus, ChromaDB, pgVector) and embedding stores.
• UseAI-powered dev tools(GitHub Copilot, Cursor, Codeium, Aider, Windsurf) to accelerate iteration.
• ImplementLLMOps / PromptOpsusing: Weights & Biases,MLflow,LangSmith,LangFuse,PromptLayer,Humanloop,Helicone,Arize Phoenix
• Benchmark and evaluate LLM systems usingRagas,DeepEval and structured evaluation suites.

Deployment & Infrastructure

• Containerize and deploy workloads withDocker, Kubernetes, KNative and managed inference endpoints.
• Optimize model performance with quantization, distillation, caching, batching and routing strategies.

Youll Bring

• Strong Python skills, with experience usingTransformers,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.

Nice to Have

• Experience withPromptOps & LLM Observabilitytools (PromptLayer, LangFuse, Humanloop, Helicone, LangSmith).
• Understanding ofResponsible 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

Seniority level

• Entry level

Employment type

• Contract

Job function

• Information Technology

Industries

• Software Development