At a Glance
- Tasks: Research and build AI tools to enhance internal workflows and usability.
- Company: Join a cutting-edge tech firm transforming trading performance with AI.
- Benefits: Competitive salary, flexible hybrid work, and rapid career growth opportunities.
- Why this job: Make a real impact by leveraging AI in a fast-paced, innovative environment.
- Qualifications: Strong academic background in AI or related fields; hands-on experience with AI tools.
- Other info: Exciting role with ownership from day one and close mentorship from senior engineers.
The predicted salary is between 34000 - 42000 ÂŁ per year.
We’re building something special, and we want the right people at the center of it. Our platform is used by tier‑one banks, hedge funds, and trading firms to identify latency bottlenecks and performance issues in high‑performance electronic trading environments. Rather than throwing money or hardware at problems, our technology pinpoints the real root causes, using insight that only comes from deep experience in trading system performance engineering and first‑hand knowledge from ex‑technical traders. We’re now entering an exciting growth phase. Alongside our existing offering, we’re developing a Cloud/SaaS platform and scaling globally, supported by industry leaders who have already validated the product as a category leader from a technical perspective.
The Role
We’re looking for an AI Tooling / Solutions Engineer to help us rapidly and safely leverage modern AI technologies to improve internal workflows, usability, and scalability. This role is not about embedding AI directly into our client‑facing product. Instead, you’ll focus on using existing AI tools, models, and frameworks to design and build supporting tooling that sits around the product, enabling internal teams (and, over time, partners) to operate it more effectively. This is a newly created, high‑impact role driven by a strategic shift. AI is now central to how we maintain our technical lead, accelerate development, and scale without compromising IP, data security, or client trust. The position would suit a highly capable graduate or early‑career engineer who enjoys applied problem‑solving, experimentation, and building practical tools that deliver real impact.
What You’ll Be Doing
- Researching and evaluating modern AI tools, models, and frameworks (e.g. LLMs, AI‑assisted development tools, orchestration frameworks)
- Identifying where AI can safely and effectively reduce complexity or manual effort
- Designing and building internal tools such as:
- Lightweight GUIs for operational tasks
- Workflow automations for engineering and support teams
- Data enrichment or metadata tooling
What This Role Is — and Isn’t
This role is:
- About using AI to build tools, not building AI products
- Focused on wrappers, interfaces, workflows, and developer tooling
- Experimental, exploratory, and delivery‑oriented
- Hands‑on: researching, prototyping, implementing, and shipping
This role is not:
- About embedding AI into a core, client‑facing product
- A long‑term blue‑sky AI research role
- A traditional DevOps, network, or domain‑specific finance role
- About building fully autonomous or agentic AI platforms
What We’re Looking For
Background
- Strong academic background, ideally a Master’s or PhD in AI, Computer Science, Software Engineering, or a related field
- Exceptional graduates with equivalent capability and hands‑on experience will also be considered
Technical Skills
- Solid software engineering fundamentals (e.g. Python, modern scripting languages, APIs, basic UI development)
- Hands‑on experience using AI tools for development or problem‑solving (e.g. LLMs, prompt engineering, model comparison, AI‑assisted coding)
- Understanding of AI limitations and trade‑offs (accuracy, cost, latency, hallucinations, data handling)
- Comfortable working with cloud‑based tools, with awareness of data governance and deployment constraints
Mindset
- Highly curious, self‑directed, and motivated to learn quickly
- Practical and delivery‑focused rather than purely theoretical
- Comfortable operating with ambiguity and minimal hand‑holding
- Excited by working in a small, fast‑moving, non‑corporate environment
Experience in financial services / capital markets beneficial but not essential.
What Success Looks Like (First 6 Months)
- Delivery of 2–3 internal tools that measurably reduce operational friction
- Clear recommendations on how and when AI tools should be used internally
- Demonstrated ability to independently research, propose, and execute solutions
- Strong working relationships with senior engineers and technical leadership
Salary & Benefits
- £40,000–£50,000 base salary (open to discussion for the right candidate)
- Flexible hybrid work set‑up
- Accelerated learning and meaningful ownership from day one
This is a shape how a highly specialised technology company adopts AI from the ground up. You’ll work on real, high‑impact engineering problems, with direct influence over the tools, workflows, and technical direction of the business. With hands‑on ownership and close exposure to senior engineers, the learning curve is far steeper than in a traditional graduate programme, offering accelerated growth and meaningful responsibility from day one.
AI Solutions Engineer employer: ISL Talent
Contact Detail:
ISL Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Solutions 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 projects, especially those involving AI tools and solutions. This gives you a chance to demonstrate your hands-on experience and problem-solving abilities to potential employers.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to AI tooling and software engineering. Be ready to discuss your thought process and how you approach problem-solving in real-world situations.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of our exciting growth phase.
We think you need these skills to ace AI Solutions Engineer
Some tips for your application 🫡
Show Your Passion for AI: When writing your application, let us see your enthusiasm for AI and how it can transform workflows. Share any personal projects or experiences that highlight your curiosity and hands-on approach to using AI tools.
Tailor Your CV and Cover Letter: Make sure your CV and cover letter are tailored to the role of AI Solutions Engineer. Highlight relevant skills like Python, AI tools, and any experience in building internal tools. We want to see how you fit into our exciting growth phase!
Be Clear and Concise: Keep your application clear and to the point. Use bullet points where possible to make it easy for us to see your key achievements and skills. Remember, we’re looking for practical problem-solvers who can communicate effectively.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this high-impact role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at ISL Talent
✨Know Your AI Tools
Make sure you’re familiar with the latest AI tools, models, and frameworks relevant to the role. Brush up on your knowledge of LLMs, AI-assisted development tools, and orchestration frameworks. Being able to discuss how these can be applied in practical scenarios will show your understanding and enthusiasm for the position.
✨Showcase Your Problem-Solving Skills
Prepare examples of past projects where you’ve used AI tools to solve real problems. Highlight your hands-on experience with Python or other scripting languages, and be ready to discuss how you approached challenges, prototyped solutions, and iterated based on feedback. This will demonstrate your practical mindset and delivery focus.
✨Understand the Trade-Offs
Be prepared to discuss the limitations and trade-offs of AI technologies, such as accuracy versus cost and latency issues. Showing that you understand these nuances will indicate that you have a pragmatic approach to applying AI in a business context, which is crucial for this role.
✨Embrace the Ambiguity
This role requires a self-directed and curious mindset. Be ready to talk about how you handle ambiguity and minimal guidance in your work. Share experiences where you’ve thrived in fast-paced environments, as this will align with the company’s culture and expectations.