Tempest Vane Partners
AI Platform Engineer

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AI Platform Engineer
Location
London
The Client
Our client is one of the world's leading investment firms, managing tens of billions of dollars across global markets. Technology sits at the heart of the organisation, powering everything from investment decision making to operational excellence.
As part of a significant investment into Artificial Intelligence, they are building a next-generation AI platform that will underpin the firm's adoption of Generative AI and autonomous systems. They are seeking an AI Platform Engineer to help define, build and scale the infrastructure that enables AI to be consumed securely and efficiently across the business.
This is a rare opportunity to join a highly technical, engineering-led environment where you'll work alongside some of the industry's brightest minds on genuinely cutting-edge problems.
What You'll Get
- Work with frontier and open-source models, including the latest LLM technologies.
- Build enterprise AI capabilities from the ground up in a greenfield environment.
- Design and deliver platforms that will be leveraged by hundreds of engineers and business users globally.
- Significant ownership across architecture, engineering and deployment.
- Collaborate with a world-class team of Software Engineers, Platform Engineers and AI specialists.
- Exposure to large-scale distributed systems, cloud technologies and modern MLOps practices.
- Competitive compensation, discretionary bonus and an exceptional benefits package.
- A culture that encourages innovation, experimentation and continuous learning.
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.
What You'll Do
- Design, build and operate scalable Python services and APIs that power AI-enabled applications.
- Deploy, fine-tune and manage commercial and open-source LLMs across production environments.
- Build cloud-native infrastructure leveraging Kubernetes and modern platform engineering principles.
- Develop tooling to support model orchestration, observability, evaluation and governance.
- Partner closely with engineering and business stakeholders to deliver practical AI solutions with measurable impact.
- Contribute to the firm's broader AI strategy, engineering standards and best practices.
- Help shape the evolution of an enterprise AI platform supporting current and future use cases, including AI agents and autonomous workflows.
What You'll Need
- Strong software engineering fundamentals with 5+ years of commercial experience.
- Excellent Python development skills and experience building production-grade services and APIs.
- Experience working with Large Language Models and modern AI frameworks (e.g. LangChain, LangGraph, DSPy, LlamaIndex, OpenAI, Anthropic or similar).
- Exposure to MLOps, model serving or AI infrastructure.
- Experience with Kubernetes and cloud-native technologies.
- Familiarity with containerisation and CI/CD pipelines.
- Experience working with distributed systems and high-availability environments.
- Excellent communication skills and the ability to engage with both technical and non-technical stakeholders.


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Nice to Have
- Experience with vector databases, RAG architectures and agentic AI systems.
- Exposure to data engineering technologies (Kafka, Airflow, Spark, etc.).
- Experience within financial services, fintech or other regulated environments.
- Knowledge of GPU infrastructure, model optimisation or inference platforms.
- Contributions to open-source projects or a demonstrable passion for AI outside of work.
Interested?
We're particularly interested in speaking with engineers who have built AI platforms rather than simply consumed APIs. If you've deployed LLMs into production, built tooling around them and enjoy solving difficult engineering problems at scale, this could be an exceptional opportunity.
Apply today or get in touch for a confidential conversation.
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