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Department: Services
Location: Remote, UK
Description
We’re looking for an Applied AI Engineer to support the design and delivery of AI-powered systems for our clients. You’ll work alongside experienced engineers, data scientists, and delivery teams to help build, test, and deploy intelligent applications, while developing your technical depth in modern AI engineering practices.
This role is ideal for someone who combines AI/ ML expertise with practical problem-solving skills and the ability to translate concepts into real-world applications.
Key Responsibilities
- Work closely with clients to understand business challenges, define AI use cases, and guide them toward the most appropriate solutions across machine learning and generative AI. Translate technical concepts into clear, actionable recommendations and support clients throughout the delivery lifecycle.
- Design, build, and deploy AI systems, including predictive models, NLP solutions, and generative AI applications such as LLM-based solutions, retrieval-augmented generation pipelines, and agentic workflows.
- Work with large structured and unstructured datasets to prepare, clean, and transform data for both traditional machine learning and generative AI use cases.
- Implement and maintain pipelines for deploying, monitoring, and managing the lifecycle of machine learning models and AI applications using cloud-native tools and frameworks.
- Collaborate with data engineers, data scientists, and cross-functional teams to deliver end-to-end AI solutions, from proof-of-concept and MVP through to production.
- Stay up to date with emerging AI and generative AI technologies, actively pursuing continuous learning, certifications, and hands-on experimentation to enhance delivery capability. Recommend improvements to tools, frameworks, and delivery approaches.
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.
Skills, Knowledge and Expertise
- Degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- Experience developing and deploying machine learning and/or generative AI solutions in production environments.
- Experience delivering end-to-end AI solutions, from proof-of-concept and MVP through to production.
- Experience working with cloud platforms (e.g. Azure, AWS, or GCP).
- Strong programming skills in Python and experience with relevant AI/ML frameworks (e.g. TensorFlow, PyTorch, Scikit-learn).
- Experience working with large structured and unstructured datasets.
- Understanding of machine learning, predictive analytics, and generative AI concepts.
- Clear communication skills and ability to work effectively in a team environment.


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Desirable:
- Strong foundational skills in AWS, event-driven architecture, CQRS, and Kafka.
- Experience designing AI architectures using AWS Bedrock.
- Previous experience working in renewable energy or highly regulated environments is beneficial.
Benefits
- Remote-first working with flexibility around client needs.
- Private Medical Insurance.
- Opportunity to work on meaningful AI projects across multiple industries.
- A collaborative culture focused on learning, excellence, and continuous improvement.
- Competitive salary with clear progression pathways.
“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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