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AI Solution Designer – Generative AI, LLMs & Intelligent Systems
We're looking for an experienced AI Solution Designer to lead the design, evaluation, and implementation of next-generation AI solutions that are scalable, safe, reliable, and impactful. This is an exciting opportunity for someone with deep expertise in AI/ML technologies, Generative AI, Large Language Models, and MLOps who can transform complex business challenges into innovative AI-driven solutions.
The Opportunity
You will play a key role in defining AI strategy and architecture, designing advanced AI systems, and guiding engineering teams through the delivery of production-grade AI solutions. Working closely with business and technical stakeholders, you will take ideas from concept through to deployment, ensuring solutions deliver measurable business value while meeting the highest standards of safety, reliability, and responsible AI.
What You'll Be Doing
- Design and develop advanced AI architectures incorporating LLMs, transformers, agent-based systems, and modern AI frameworks
- Lead the design of scalable AI solutions aligned with business objectives
- Architect AI components including RAG pipelines, vector databases, orchestration frameworks, and intelligent agents
- Define standards for model architecture, prompt engineering, and AI pipeline optimisation
- Establish AI evaluation frameworks, performance metrics, validation methodologies, and safety controls
- Ensure AI solutions meet reliability, governance, ethical, and regulatory requirements
- Drive MLOps best practices covering continuous training, testing, deployment, monitoring, and lifecycle management
- Guide infrastructure and platform decisions to ensure AI services are scalable, secure, and production-ready
- Collaborate with stakeholders to define solution direction and clearly communicate architectural decisions
- Provide technical leadership, mentoring, and strategic guidance across AI initiatives
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Key Skills & Experience
AI & Machine Learning
- Strong academic background with a Master's or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline
- Deep understanding of machine learning, deep learning, and AI systems design
- Strong knowledge of large language models, transformer architectures, NLP, reinforcement learning, and modern AI methodologies
- Experience working with Graph Databases and knowledge-driven AI architectures
- Expertise designing enterprise-grade Generative AI solutions
Programming & Engineering
- Expert-level Python development
- Strong experience with TensorFlow, PyTorch, or equivalent ML frameworks
- Experience building scalable and production-ready AI platforms
- Strong data engineering knowledge including ETL processes and feature engineering


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Generative AI & Intelligent Systems
- LLM architecture and implementation
- Retrieval-Augmented Generation (RAG)
- Vector databases and embeddings
- Agent frameworks and orchestration
- AI evaluation frameworks and testing methodologies
- Prompt engineering and optimisation
- AI safety, reliability, and governance practices
MLOps & Deployment
- End-to-end AI model lifecycle management
- Model versioning, CI/CD, and automated deployment
- Experience with modern MLOps toolchains
- Cloud-based AI deployment and operationalisation
- Monitoring, testing, and continuous improvement of production AI systems
Nice to Have
- Experience leading enterprise AI transformation initiatives
- Background in AI governance and responsible AI frameworks
- Experience with cloud-native AI platforms and AWS-based AI services
- Exposure to knowledge graphs and semantic AI architectures
- Experience mentoring AI engineers, data scientists, and technical teams
- Track record of delivering AI solutions into large-scale enterprise environments
If you're passionate about Generative AI, LLMs, intelligent agents, and building innovative AI solutions that create real business impact, we'd love to hear from you.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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