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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, making a real impact on client success.
- 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 technology.
The predicted salary is between 72000 - 108000 £ per year.
Remote First, with 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
- Reusable Assets & Consulting Capability Building: As part of a consulting-led engineering practice, you will:
- 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
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
Senior Consulting Engineer (LLM & Agentic AI) employer: Staffworx Limited
Contact Detail:
Staffworx Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Consulting Engineer (LLM & Agentic AI)
✨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, multi-agent systems, and AI engineering. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common technical questions and case studies relevant to AI consulting. Be ready to discuss how you've tackled complex problems in the past and how you can apply that experience to their needs.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your hands-on experience and client-facing skills, and let us know why you're excited about the role.
We think you need these skills to ace Senior Consulting Engineer (LLM & Agentic AI)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Consulting Engineer role. 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 makes you a perfect fit for this role. Don’t forget to mention specific projects or achievements that showcase your expertise.
Showcase Your Client Engagement Skills: Since this role involves working closely with clients, make sure to highlight any previous experience where you've successfully translated complex problems into effective solutions. We love seeing examples of how you've built strong client relationships in the past!
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 gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Staffworx Limited
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLMs, embeddings, and multi-agent 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 problems into feasible engineering solutions. Prepare examples of how you've successfully engaged with clients in the past and how you’ve addressed their unique challenges.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios during the interview. Think about how you would approach ambiguous client problems and what frameworks or methodologies you would use to find solutions. This will highlight your critical thinking and adaptability.
✨Demonstrate Team Collaboration
This role requires working closely with consulting teams and client stakeholders. Share experiences where you’ve collaborated effectively with others, especially in cross-functional settings. Highlight your ability to influence and lead technical discussions to ensure successful project outcomes.
