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- Tasks: Design and deploy scalable AI/ML solutions that enhance platform efficiency and decision-making.
- Company: Global investment organisation with a cutting-edge technology estate.
- Benefits: Industry-leading compensation, professional growth, and a balanced work environment.
- Why this job: Make a real impact on technology-driven finance with your AI solutions.
- Qualifications: 4+ years in software or AI/ML engineering, strong Python skills, and experience with AI frameworks.
- Other info: Collaborative culture with talented engineers and opportunities for career development.
The predicted salary is between 48000 - 72000 £ per year.
A global investment organisation with a highly sophisticated technology estate is hiring an AI-driven Platform Engineer to sit at the core of its engineering enablement strategy. This role focuses on building reusable AI platforms and agentic systems that materially change how software is designed, tested, and delivered across the firm.
This is not a research or proof-of-concept role. The successful candidate will operate in a production-first environment, delivering scalable AI capabilities used daily by engineering teams, where cutting-edge AI and software engineering directly impact high-stakes financial systems.
In this role, you’ll design, build, and deploy scalable AI/ML solutions that improve platform efficiency and decision-making. You’ll work with modern technologies including Python, AI agent frameworks (OpenAI, LangChain), Kubernetes, and cloud-based infrastructure, while driving automation and developer productivity.
Why Join
- Impactful work: Your AI/ML solutions are deployed in production to optimise trading strategies and critical systems.
- Tech-forward environment: Access to advanced AI frameworks, cloud infrastructure, containers, CI/CD, and distributed systems.
- Collaborative culture: Work alongside talented engineers, quants, and researchers in a supportive, intellectually curious environment.
- Professional growth: Tackle complex engineering challenges, explore new AI tools, and expand your technical expertise.
- Balanced environment: A culture that values innovation, collaboration, and career development.
Compensation and Benefits: Industry-leading. Here, your contributions as an AI Software Engineer go beyond coding; they help shape the future of technology-driven finance.
What You'll Need
- A minimum of 4 years in software, platform, or AI/ML engineering with hands-on experience in automation, infrastructure as code, or boosting developer productivity.
- Strong coding skills in Python, plus at least one other object-oriented language (C#, Java, C++, Go).
- Deep experience with AI agent frameworks like OpenAI Agents SDK, Claude Agents SDK, or LangChain.
- A Computer Science or STEM-related degree.
- Proven track record deploying AI/ML solutions in production at scale.
- Expert in CI/CD pipelines, infrastructure as code, and distributed systems.
- Skilled in designing scalable, reliable, and testable software and infrastructure.
- Advanced knowledge of containers and Kubernetes orchestration.
- Hands-on with Terraform, Kubernetes Operators, or similar configuration/infrastructure tools.
- Comfortable working across cloud (AWS preferred) and on-premises environments.
If you’re a motivated AI Software Engineer looking to step into an ideas-driven, high-performance environment, we’d love to hear from you.
Artificial Intelligence Engineer employer: Tempest Vane Partners
Contact Detail:
Tempest Vane Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those that demonstrate your ability to deliver scalable solutions. This will give you an edge and make you memorable during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding the latest AI frameworks. Practice common algorithms and system design questions to feel confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Artificial Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML engineering and the specific technologies mentioned in the job description. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for this role. Share your passion for AI and how your previous experiences have prepared you for this position. Keep it engaging and personal – we love to see your personality shine through!
Showcase Your Projects: If you've worked on any AI platforms or automation projects, make sure to include them in your application. We’re keen to see real-world examples of your work, especially those that demonstrate your ability to deliver scalable solutions in production environments.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Tempest Vane Partners
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and AI agent frameworks like OpenAI and LangChain. Brush up on your knowledge of Kubernetes and cloud infrastructure too, as these will likely come up during technical discussions.
✨Showcase Real-World Experience
Prepare to discuss specific projects where you've deployed AI/ML solutions in production. Highlight how your contributions improved efficiency or decision-making, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Problem-Solving Skills
Expect to tackle some technical problems during the interview. Practice coding challenges and system design questions that focus on scalability and reliability. This will show your ability to think critically and apply your skills in a real-world context.
✨Emphasise Collaboration and Growth
Since the role involves working with engineers, quants, and researchers, be prepared to discuss how you’ve collaborated in past roles. Share examples of how you’ve contributed to a team environment and your eagerness to learn and grow within a tech-forward culture.
