Hire(d) better.
Hire(d) better.
Hire(d) better.
Remote (UK-based) | Full-Time
Reactive Markets is the 2026 OTC Trading Platform of the Year (Risk.net). Our network handles over $50 billion in daily trading volumes across FX, Equities, and Cryptocurrency, connecting 40+ of the world's leading liquidity providers.
We build trading systems that operate at the edge of what's technically possible — where nanoseconds matter and a dropped message costs real money. Our engineering team is small, senior, and deeply invested in the craft of building cutting edge, reliable, high-performance systems.
We're looking for a full-stack engineer who can build AI-powered tools and data infrastructure that make our platform smarter, our people more effective, and our operations more scalable.
This is not a research role. You'll build real systems that people use every day — Slack bots that investigate production incidents, data pipelines that surface anomalies before clients notice them, and AI agents that turn hours of manual trawling into seconds of guided investigation. You'll work across the full stack: Python and TypeScript for AI tooling and integrations, Go for backend services, and SQL for data analysis and pipeline work.
The person we're looking for ships working software, cares about making people's lives easier, and is energised by the pace of the AI landscape. You don't need to have built LLM applications before — but you should be curious, practical, and comfortable learning fast.
You'll work closely with our TechOps, Connectivity, and Data teams to understand their workflows, pain points, and knowledge gaps — then build the tools and infrastructure that solve them. This is a high-leverage role: the systems you build will multiply the effectiveness of every engineer and operator in the company.
AI-powered investigation tools — Slack-based bots and agents that automatically analyse support tickets, query production logs, and surface relevant context for incident response
MCP (Model Context Protocol) servers — authenticated access to ClickHouse, Kubernetes, Atlassian, and GitHub, enabling AI agents to interact with real systems safely
Data infrastructure — ClickHouse analytics pipelines, real-time anomaly detection, and platform health monitoring (our "Radar" initiative)
AI agent development — constrained, repeatable diagnosis agents that follow investigation playbooks, produce structured outputs, and operate with appropriate guardrails
Knowledge engineering — building and curating the corpus that makes our AI tools accurate: documentation, training material, structured metadata, and feedback loops
Internal tooling — full-stack applications that bridge the gap between data, AI, and the people who need answers
Technical:
Strong Python — your primary language for AI tooling, data pipelines, and backend services
TypeScript / JavaScript — for Slack integrations, web interfaces, and full-stack tooling
Go experience is a bonus — we use Go extensively for backend services and CLI tooling
SQL — comfortable writing analytical queries against large datasets (ClickHouse, PostgreSQL, or similar)
Familiarity with LLM APIs and tooling — Claude, OpenAI, or similar; prompt engineering, function calling, tool use
Experience with Docker, Kubernetes, and AWS — your tools will run in production infrastructure
Git and Linux fundamentals
Experience in financial services is a plus but not essential — domain knowledge can be learned; engineering instinct cannot
How you work:
You ship. You're delivery-focused — you iterate quickly, you get things in front of users, you improve based on feedback
You bridge domains. You're comfortable moving between AI, data, infrastructure, and product. You don't wait for someone else to define the interface — you go and understand the problem yourself
You own it. When you build something, you take responsibility for its behaviour in production. You monitor it, you fix it, you make it better
You write things down. Documentation is how we scale knowledge across a distributed team. Good documentation also makes our AI tools better — every well-written page becomes training material
You communicate. We're a distributed team across multiple time zones. Clear, proactive communication is essential
You embrace AI as a tool. You use AI to amplify your own productivity — and you build tools that do the same for others
Greenfield AI work — you're not maintaining legacy systems; you're building the next generation of intelligent tooling for a trading platform
Real impact — the tools you build will be used daily by engineers, operators, and eventually clients. This is not a side project
An excellent team — senior engineers who care about craft, collaborate openly, and hold each other to high standards
Ownership — small teams, clear accountability, direct impact on the platform and our people
Competitive package — up to 30 days leave + bank holidays, private health insurance, pension, life insurance, dental/optical cashback, cycle to work, socials and offsites
Remote-friendly — work from home with flexibility. We trust our people to deliver
Sustainable pace — we work hard, but we don't burn people out. Balance is how we stay sharp
Growth — this role sits at the intersection of AI, data, and platform engineering. As the company scales, so does the opportunity
We believe in transparency, honest feedback, and writing things down. We celebrate delivery, not activity. We frame AI as empowering people — removing toil, amplifying capability, enabling higher-value work.
We keep our process focused and respectful of your time. Our process follows three stages.
Stage 1: Initial Conversation with Talent Acquisition
Format: Video call, ~30-45 minutes
Stage 2: Hiring Manager Conversation with the relevant team lead or hiring manager
Format: Video call, ~60 minutes
Stage 3: Technical Interview with two members of the relevant engineering team
Format: Video call, interactive session. ~60 minutes
What to expect in each stage will be explained by Talent Acquisition if you're invited to interview. Throughout the process, we aim to keep momentum with no unnecessary delays between stages, and feedback typically comes within a few business days.
*Please note that depending on availability, Stage 2 and 3 may swap around.
Please apply directly via this job posting — all applications, including those submitted via LinkedIn, are managed through our applicant tracking system, so you'll always land in the same place regardless of where you found this role.
Right to Work: Candidates must have the existing right to work in the UK. We are not currently able to offer visa sponsorship for this role.
Equal Opportunities: Reactive Markets is an equal opportunities employer. We welcome applications from all qualified candidates regardless of age, disability, gender reassignment, marriage or civil partnership, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.
Reasonable Adjustments: If you need any adjustments or support during the application or interview process, please let us know — we're happy to accommodate.
Data Protection: By applying, you consent to Reactive Markets processing your personal data for recruitment purposes, in line with our privacy policy.
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Will AI replace this role?
Check AI displacement risk, transferable skills, and career alternatives for AI & Data Engineer
The AI & Data Engineer position at Reactivemarkets is based in Remote, UK. This is a remote position.
The AI & Data Engineer position at Reactivemarkets is a Full time role.
Key skills for the AI & Data Engineer position at Reactivemarkets include: python, typescript, sql, large language models, kubernetes, github, javascript, postgres, docker, aws.
