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For Companies At a Glance
- Tasks: Design and optimise AI systems using cutting-edge prompt engineering techniques.
- Company: Join a forward-thinking UK-based talent partner in the tech industry.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
- Why this job: Be at the forefront of AI innovation and make a real impact in technology.
- Qualifications: Strong Python skills and a passion for AI/ML technologies.
- Other info: Dynamic role with excellent career advancement potential in a rapidly evolving field.
The predicted salary is between 36000 - 60000 £ per year.
Design, optimize, and operationalize prompt-driven and agentic AI systems. Architect LLM-powered workflows that connect people, data, and intelligent systems in high-impact, production-ready ways.
THE ROLE
- Prompting, Reasoning & Agentic Systems
- Design, test, and optimize prompts for leading frontier models (GPT-4.x/5, Claude 3+, Gemini, LLaMA, DeepSeek, and emerging open-weight models).
- Apply advanced prompting and reasoning techniques, including:
- Chain-of-Thought, ReAct, Tree-of-Thoughts, Graph-of-Thoughts, Program-of-Thoughts
- Self-reflection and critique loops
- Debate prompting and multi-agent collaboration
- Architect agentic workflows using frameworks such as AutoGen, CrewAI, LangGraph, and custom orchestration layers.
- Build systems with tool calling, long-term and short-term memory, retrieval pipelines, and structured reasoning constraints.
- Integrate LLMs into real-world applications using LangChain, LlamaIndex, Haystack, AutoGen, and OpenAI Assistant / Responses API patterns.
- Design and implement high-performance Retrieval-Augmented Generation (RAG) pipelines, including:
- Hybrid (keyword + vector) search
- Reranking and embedding optimization
- Chunking and document preprocessing strategies
- Work across AI/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io.
- Deploy and manage vector databases and embedding stores, including Pinecone, Weaviate, Milvus, FAISS, ChromaDB, and pgVector.
- Implement LLMOps / PromptOps practices using tools such as:
- Weights & Biases, MLflow, LangSmith, LangFuse, PromptLayer, Humanloop, Helicone, Arize Phoenix
- Containerize and deploy GenAI workloads using Docker, Kubernetes, KNative, and managed inference endpoints.
- Optimize system performance with:
- Caching, batching, routing, and fallback strategies
- Quantization and distillation for efficient inference
- Cost, latency, and reliability optimization
EXPERIENCE
- Strong Python engineering skills with hands-on experience across the modern GenAI ecosystem.
- Deep understanding of LLM behaviour, prompt optimization, embeddings, retrieval strategies, and data preparation workflows.
- Practical experience with vector databases and semantic search systems.
- Comfortable working in Linux environments with Bash/PowerShell, containers, and cloud infrastructure.
- Strong communication skills, creativity, and a systems-thinking mindset.
- Curious, adaptable, and motivated to stay ahead of rapid advances in GenAI and AI-native software development.
BENEFICIAL
- Experience with PromptOps, LLM observability, and evaluation tooling.
- Understanding of Responsible AI, safety, bias mitigation, governance, and compliance frameworks.
- Background in Computer Science, AI/ML, Engineering, or a related technical discipline.
- Experience deploying, fine-tuning, or serving open-source LLMs in production.
Staffworx is a UK-based Talent & Recruiting Partner supporting organisations across Digital Commerce, Software Engineering, and Value-Add Consulting sectors throughout the UK & EMEA.
AI Prompt Engineer in London employer: Staffworx
Contact Detail:
Staffworx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Prompt Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech space, attend meetups, and join online communities. The more connections we make, the better our chances of landing that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your prompt engineering projects and any cool AI systems you've built. This gives us a chance to demonstrate our expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common questions related to AI and prompt engineering. We should also be ready to discuss our thought process and problem-solving techniques in detail.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our applications to highlight how our skills align with the job description.
We think you need these skills to ace AI Prompt Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Prompt Engineer role. Highlight your experience with prompt engineering and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Show Off Your Technical Skills: Don’t hold back on showcasing your Python engineering skills and familiarity with GenAI tools. Mention specific frameworks or models you’ve worked with, like GPT-4.x or LangChain. This is your chance to impress us with your technical prowess!
Be Creative in Your Approach: We love creativity! When describing your past experiences, think outside the box. Use examples that demonstrate your problem-solving skills and innovative thinking, especially in designing agentic workflows or optimising prompts.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Staffworx
✨Know Your Models
Familiarise yourself with the latest AI models mentioned in the job description, like GPT-4.x and Claude 3+. Be ready to discuss their strengths and weaknesses, and how you would apply advanced prompting techniques to optimise their performance.
✨Showcase Your Workflow Skills
Prepare to explain how you would architect agentic workflows using frameworks like AutoGen or LangGraph. Bring examples of past projects where you've integrated LLMs into real-world applications, highlighting your problem-solving skills and creativity.
✨Demonstrate Technical Proficiency
Brush up on your Python skills and be ready to discuss your experience with vector databases and cloud platforms. They might ask you to solve a technical problem on the spot, so practice coding challenges related to AI/ML systems.
✨Communicate Clearly
Strong communication is key! Practice explaining complex concepts in simple terms. Be prepared to discuss how you approach collaboration in multi-agent systems and how you ensure responsible AI practices in your work.