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For Companies At a Glance
- Tasks: Design and deliver cutting-edge AI systems for clients, tackling complex challenges with innovative solutions.
- Company: Join a forward-thinking consulting firm at the forefront of AI engineering.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Be a key player in transforming businesses with AI technology and make a real impact.
- Qualifications: 6-8 years in software or AI engineering, strong Python skills, and client-facing experience.
- Other info: Dynamic role with opportunities to shape the future of AI consulting.
The predicted salary is between 72000 - 108000 £ per year.
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
- 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
- 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
- Build reusable accelerators, agent patterns and technical templates for client delivery
- Contribute to internal playbooks, training and enablement programmes
- Share emerging research, frameworks and deep-tech insights with consulting teams
- Influence delivery methodology, technical standards and architectural patterns
Experience & Skills: This is a senior, hands-on consulting engineering role. Candidates should bring:
- 6 to 8 years’ 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
LLM & Agentic Consulting Engineer in England employer: Staffworx
Contact Detail:
Staffworx Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM & Agentic Consulting Engineer in England
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and consulting space. Attend meetups, webinars, or industry events to meet potential employers and showcase your skills. Remember, it’s all about who you know!
✨Tip Number 2
Show off your expertise! Create a portfolio that highlights your projects related to LLMs, agentic systems, and AI engineering. Share it on platforms like LinkedIn or even our StudySmarter website to catch the eye of recruiters looking for talent.
✨Tip Number 3
Prepare for those interviews! Research common questions related to AI systems and consulting roles. Practice articulating your experience with multi-agent architectures and retrieval systems so you can impress the interviewers with your knowledge.
✨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, so make sure to check us out!
We think you need these skills to ace LLM & Agentic Consulting Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your hands-on experience with LLMs, multi-agent systems, and any relevant cloud AI ecosystems. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI engineering and how your background aligns with our mission at StudySmarter. Be sure to mention specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills: In your application, don’t shy away from detailing your technical skills. Whether it's Python programming or designing retrieval architectures, we want to know what you can do. Include examples of past projects where you've successfully implemented these skills.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. This way, your application will be in the right hands, and we can get back to you quicker. Plus, it shows you're keen on joining us at StudySmarter!
How to prepare for a job interview at Staffworx
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest AI technologies, especially LLMs and multi-agent systems. Brush up on your Python skills and be ready to discuss your hands-on experience with production-grade systems. The more you can demonstrate your technical prowess, the better!
✨Understand Client Needs
Before the interview, research the company’s clients and their challenges. Be prepared to discuss how you would translate complex business problems into feasible engineering solutions. Showing that you can think from the client’s perspective will set you apart.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled ambiguous problems in the past. Think about specific projects where you assessed data, platforms, or security constraints. Being able to articulate your thought process will highlight your consulting capabilities.
✨Demonstrate Collaboration and Leadership
This role requires working closely with clients and internal teams. Share experiences where you led technical design discussions or collaborated with domain experts. Emphasising your ability to influence and guide others will resonate well with interviewers.
