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:
o Lightweight GUIs for operational tasks
o Workflow automations for engineering and support teams
o Data enrichment or metadata tooling
o Prototyping quickly, validating with users, and iterating towards production‑ready solutions
o Advising on model selection, cost vs performance trade‑offs, and deployment considerations (cloud vs on‑prem)
o Acting as an internal point of reference for “what’s possible now” in applied AI, with a pragmatic, non‑hype‑driven mindset
o Documenting tools, decisions, and lightweight roadmaps
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.
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