AI Solutions Engineer

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.

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.

• 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
  • Prototyping quickly, validating with users, and iterating towards production‑ready solutions
  • Advising on model selection, cost vs performance trade‑offs, and deployment considerations (cloud vs on‑prem)
  • Acting as an internal point of reference for “what’s possible now” in applied AI, with a pragmatic, non‑hype‑driven mindset
  • Documenting tools, decisions, and lightweight roadmaps

• About us ing 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

• About embedding AI into a core, client‑facing product
• A long‑term blue‑sky AI research role
• A traditional Dev Ops, network, or domain‑specific finance role
• About building fully autonomous or agentic AI platforms

• 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

• 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

• 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

• Delivery of 2–3 internal tools that measurably reduce operational friction
• Clear recommendations on how and when AI tools should be used…