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- Tasks: Design and optimise AI systems using cutting-edge prompt engineering techniques.
- Company: Join a forward-thinking UK-based talent and recruiting partner.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of GenAI technology and make a real impact.
- Qualifications: Strong Python skills and experience with modern GenAI ecosystems required.
- Other info: Dynamic role with excellent career advancement 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
- 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
- Evaluation and regression testing harnesses
- 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 behavior, 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 Engineer (Remote) in London employer: Staffworx
Contact Detail:
Staffworx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech space on LinkedIn or at meetups. We can’t stress enough how personal connections can lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving prompt engineering and LLMs. We love seeing real-world applications of your work, so make it shine!
✨Tip Number 3
Prepare for interviews by practising common questions related to AI systems and prompt optimisation. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for talent that fits our vision.
We think you need these skills to ace AI Engineer (Remote) in London
Some tips for your application 🫡
Show Off Your Skills: When you're writing your application, make sure to highlight your Python engineering skills and any hands-on experience you've got with GenAI. We want to see how you can design and optimise those prompt-driven AI systems!
Tailor Your Application: Don’t just send a generic application! Tailor it to the role by mentioning specific techniques like Chain-of-Thought or RAG pipelines that you’ve worked with. This shows us you’re not just interested, but you really get what we’re about.
Be Creative and Curious: We love creativity and a curious mindset! Share examples of how you've approached problem-solving in the past, especially in AI/ML contexts. Let us know how you stay ahead of trends in GenAI – we’re all about innovation!
Apply Through Our Website: Make sure to apply through our website for the best chance of getting noticed! It’s the easiest way for us to keep track of your application and ensure it lands in the right hands.
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 Projects
Prepare to talk about specific projects where you've designed or optimised prompt-driven AI systems. Highlight your experience with frameworks like LangChain or AutoGen, and be ready to explain your thought process and the impact of your work.
✨Demonstrate Systems Thinking
This role requires a systems-minded approach, so be prepared to discuss how you architect workflows that connect people, data, and intelligent systems. Use examples from your past experiences to illustrate your ability to design resilient and observable GenAI systems.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to GenAI and their expectations for the role. This shows your genuine interest and helps you gauge if the company aligns with your career goals and values.