Quant Capital
AI Engineer

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AI Engineer
Quant Capital is working with an innovative technology-driven business looking to hire an AI Engineer to join a high-performing engineering team. This is an opportunity to work on challenging AI problems where machine learning, large language models and software engineering come together. The team operates with a high degree of autonomy, giving engineers genuine ownership over the systems they build and the opportunity to take ideas from initial concept through to production. The focus is firmly on building useful, reliable AI systems rather than experimental prototypes. You will work across the full AI development lifecycle, from data and model development through to deployment, evaluation and ongoing optimisation.
The Role
As an AI Engineer, you will help design and develop intelligent systems that solve complex real-world problems. You will work closely with engineers and product-focused teams, contributing to both the technical direction and implementation of new AI capabilities.
Key Responsibilities
- Design, develop and deploy production-grade AI and machine learning systems.
- Build LLM-powered applications, including agentic workflows, tool use and multi-step reasoning systems.
- Develop and improve models across areas such as natural language processing, structured data and other machine learning applications.
- Experiment with different models and approaches, assessing their performance, reliability, latency and cost.
- Develop systems for prompt engineering, model adaptation, fine-tuning and retrieval where appropriate.
- Build robust evaluation frameworks to measure model performance and identify areas for improvement.
- Work with large and potentially messy datasets to extract useful information and develop intelligent solutions.
- Design reliable software around inherently non-deterministic AI models, with appropriate monitoring, testing and safeguards.
- Take ownership of projects from initial problem definition through development, deployment and iteration.
- Work alongside software engineers and product teams to turn complex requirements into scalable technical solutions.
- Continuously investigate new AI technologies, frameworks and approaches and assess where they can provide genuine value.
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.
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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.
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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.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We're Looking For
- Strong software engineering fundamentals and experience developing production-quality systems.
- Strong Python skills and a solid understanding of software design principles.
- Commercial or substantial project experience working with machine learning, AI or LLM-based systems.
- Experience building and deploying AI/ML applications rather than working solely with research prototypes.
- Good understanding of modern LLM concepts, including prompting, embeddings, retrieval, agents, tool use and model evaluation.
- Experience with one or more machine learning frameworks and familiarity with modern AI development tooling.
- Strong data skills, with experience working with structured and unstructured data.
- An understanding of the practical trade-offs involved in AI systems, including accuracy, latency, scalability, reliability and cost.
- A strong analytical approach and the ability to break down complex technical problems.
- Experience designing APIs, backend services or other production software would be advantageous.
- A degree in Computer Science, Mathematics, Engineering, Physics or another highly quantitative/technical discipline is preferred.


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The Person
We are looking for someone who enjoys building rather than simply discussing technology. You should be comfortable working in an environment where problems are not always clearly defined and where you are expected to take ownership of finding the right solution. You will be encouraged to experiment, challenge existing approaches and bring new ideas to the team. At the same time, you should understand the difference between an impressive demonstration and a system that can be trusted in production. Strong communication skills are important, as you will work across engineering and product teams and will need to explain technical decisions clearly.
Why Join?
- High level of technical ownership and autonomy.
- Opportunity to work on cutting-edge AI and LLM applications.
- Exposure to the full lifecycle of production AI systems.
- Small, highly technical engineering environment.
- Opportunity to influence architecture, tooling and technical direction.
- Work alongside experienced engineers solving genuinely complex problems.
- Strong scope for professional and technical development.
Location: London
Salary: Competitive, depending on experience
Package: Competitive salary and benefits
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