
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
AI Architect – Job Description
Role Overview
We are seeking an experienced AI Architect to lead the design, development, and deployment of advanced Artificial Intelligence and Generative AI solutions. The ideal candidate will combine deep technical expertise with strong business acumen, translating complex and ambiguous business challenges into scalable AI-driven solutions that deliver measurable value.
Key Responsibilities
- Architect, design, and implement enterprise-grade AI and Generative AI solutions across a range of business domains.
- Collaborate with business stakeholders to understand requirements and translate complex problems into structured AI/ML architectures and delivery roadmaps.
- Design and optimise Retrieval-Augmented Generation (RAG) frameworks, vector database architectures, embedding strategies, and agentic AI workflows.
- Develop and integrate solutions leveraging Large Language Models (LLMs), foundation models, and Model Context Protocol (MCP) frameworks.
- Lead the selection and implementation of AI platforms, tools, and frameworks, ensuring scalability, security, and operational excellence.
- Build and maintain robust data pipelines using SQL, Python, and modern data engineering practices.
- Develop advanced analytics capabilities including anomaly detection, causal inference, predictive modelling, and machine learning solutions.
- Work closely with engineering, product, and business teams to deliver AI initiatives across multiple projects in a fast-paced environment.
- Create compelling data visualisations, dashboards, and presentations to communicate insights and solution outcomes to technical and non-technical stakeholders.
- Provide technical leadership, mentoring, and best-practice guidance to development and data science teams.
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.
Required Skills & Experience
- Strong experience in data engineering, with advanced proficiency in Python and SQL.
- Hands-on experience with Large Language Models (LLMs), foundation models, prompt engineering, embeddings, vector databases, and RAG architectures.
- Proven experience designing and implementing agentic AI systems, including MCP (Model Context Protocol) integrations.
- Strong knowledge of Generative AI frameworks such as LangChain, LlamaIndex, and related orchestration platforms.
- Experience developing and deploying machine learning models, including anomaly detection and causal inference solutions.
- Demonstrated ability to translate ambiguous business requirements into practical AI and machine learning solutions.
- Strong communication and stakeholder management skills, with the ability to explain complex technical concepts to diverse audiences.
- Experience managing multiple initiatives simultaneously while delivering high-quality outcomes.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
Preferred Qualifications
- Experience with cloud AI platforms such as Azure AI Services, Azure Machine Learning, AWS, or Google Cloud AI.
- Knowledge of MLOps, model governance, responsible AI principles, and AI security best practices.
- Experience leading AI strategy, architecture reviews, and enterprise-scale AI transformation programmes.
Key Competencies
- AI & Solution Architecture
- Generative AI & LLM Engineering
- Data Engineering & Analytics
- Problem Solving & Critical Thinking
- Stakeholder Management
- Technical Leadership
- Communication & Storytelling
- Innovation & Continuous Learning
“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
Skills
Location