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- Tasks: Design and deliver cutting-edge AI systems for clients, tackling complex challenges with innovative solutions.
- Company: Join a forward-thinking consulting firm leading the charge in AI engineering.
- Benefits: Remote-first work, competitive salary, and opportunities for professional growth.
- Why this job: Be at the forefront of AI transformation and make a real impact on client success.
- Qualifications: Experience in software and AI engineering, especially with LLMs and multi-agent systems.
- Other info: Dynamic role with excellent career advancement opportunities in a rapidly evolving field.
The predicted salary is between 36000 - 60000 £ per year.
Remote First, some trips to client offices and HQ.
Lead the design and delivery of complex, AI-native client engagements, spanning agentic systems, retrieval architectures and semantic layers. This is a senior, hands-on consulting role combining deep technical leadership with strong client presence, shaping both client outcomes and the firm’s long-term AI engineering capability.
As client demand for AI-native transformation accelerates, the consulting practice is expanding its engineering capability across agentic systems, retrieval, ontologies and AI-enabled execution. The Consulting Engineer is a hands-on AI systems builder who combines deep engineering craft with commercial and product thinking to design, build and deploy agentic, retrieval and ontology-based systems for enterprise clients. You will work directly with senior client stakeholders and alongside consulting and orchestration roles, translating complex business challenges into safe, reliable and measurable AI solutions.
Key Accountabilities- Client-Facing AI Engineering & Agentic System Design: You will design and deliver production-grade AI systems for external clients, including:
- LLM applications using modern orchestration patterns, prompt frameworks and evaluation loops
- Multi-agent architectures, including planning, delegation, safety constraints and monitoring
- Retrieval and vector-based systems, embeddings, structured reasoning and semantic workflows
- Ontology and knowledge modelling literacy to enable precise reasoning and data alignment
- Integrations and automation via APIs, tools and enterprise systems
- Prompt engineering at scale, including pattern libraries, guardrails and explainability checks
- Technical Discovery, Feasibility & Solution Architecture: Working closely with consulting counterparts, you will:
- Translate ambiguous client problems into clear, feasible engineering approaches
- Assess client data, platforms, security constraints and operating models
- Contribute to framing, use-case shaping and technical scoping discussions
- Work directly with client domain experts to surface edge cases and operational realities
- Produce clear, lightweight technical artefacts for client and internal audiences
- Delivery Excellence, AI Ops & Reliability: You will ensure client solutions are safe, observable and enterprise-ready by:
- Implementing evaluation frameworks and safety checks across models and agents
- Designing monitoring, logging, tracing and incident-response patterns
- Applying governance, risk and compliance principles within client environments
- Supporting releases, environments and handover into client operations
- Ensuring reliability, reproducibility, performance and cost controls
This is a senior, hands-on consulting engineering role. Candidates should bring:
- Solid experience in software engineering, AI engineering, or applied data engineering
- Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector databases
- Experience designing or implementing multi-agent systems or tool-calling frameworks
- Strong Python skills with experience building production-grade systems
- Experience working across at least one major cloud AI ecosystem (e.g. Azure/OpenAI, GCP/Vertex, AWS, Anthropic)
- Familiarity with semantic modelling, ontologies, or knowledge graph concepts
- Proven ability to rapidly prototype solutions for client validation
- Experience working directly with clients in consulting or professional services contexts
Staffworx are a UK based Talent & Recruiting Partner, supporting Digital Commerce, Software and Business Consulting sectors across the UK & EMEA.
LLM, RAG & Agentic AI Engineer in London employer: Staffworx
Contact Detail:
Staffworx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM, RAG & Agentic AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and consulting space. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your projects related to LLMs, agentic systems, and retrieval architectures. This will not only impress potential employers but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding multi-agent systems. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with clients and stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who can lead AI-native transformations. Your next big opportunity could be just a click away!
We think you need these skills to ace LLM, RAG & Agentic AI Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of LLM, RAG & Agentic AI Engineer. Highlight your experience with AI systems, multi-agent architectures, and any relevant projects that showcase your skills in software engineering and client engagement.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of how you've tackled complex engineering challenges and how your background aligns with our focus on AI-native transformation.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Include details about your hands-on experience with LLMs, embeddings, and any cloud AI ecosystems you’ve worked with. We want to see your engineering craft in action!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you into our system quickly!
How to prepare for a job interview at Staffworx
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, retrieval architectures, and agentic systems. Be ready to discuss specific projects you've worked on that showcase your hands-on experience with these technologies. The more you can demonstrate your technical expertise, the better!
✨Understand Client Needs
Since this role involves a lot of client interaction, it's crucial to show that you can translate complex business challenges into AI solutions. Prepare examples of how you've successfully engaged with clients in the past and how you approached their unique problems.
✨Showcase Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios during the interview. Think about how you would assess client data or design a solution for a specific challenge. This will highlight your ability to think critically and apply your engineering skills in real-world situations.
✨Communicate Clearly
Strong communication is key in consulting roles. Practice explaining complex concepts in simple terms, as you'll need to convey technical information to non-technical stakeholders. Clear communication can set you apart from other candidates!