Lead AI Engineer

About RedCloud

The global supply chain is broken creating a $2 trillion inventory gap where essential consumer goods fail to reach the people who need them. Brands miss sales, distributors mismanage stock, and retailers face empty shelves. The result is higher prices, slower growth, and lost opportunity across the board. RedCloud is fixing this. Our RedAI digital trading platform, bulk and retail trading exchanges connect key parts of the supply chain—enabling bulk inventory exchange, streamlined digital payments, and generating vast quantities of aggregated market data. By applying AI and machine learning techniques, we deliver predictive market insight and trading recommendations straight back to the trading environment—facilitating smarter everyday business decisions for our customers, from factory to warehouse to store. Headquartered in London, RedCloud became a publicly listed company on Nasdaq (RCT) in March 2025. With a diverse team spanning many nationalities and operations across Africa, the Middle East, Europe, and Latin America, we’re building a more connected and efficient global trade network.

The Role

We are seeking a highly experienced AI Lead who combines deep technical expertise with team leadership. In this role, you will design, build, and maintain AI/ML capabilities, models, and LLM‑powered solutions that power our products and customer experiences. You will lead a squad of AI engineers and data scientists, ensuring high‑quality delivery while fostering a culture of accountability, innovation, and continuous improvement. Working closely with product managers and engineering leadership, you will guide architectural decisions, support delivery excellence, and ensure AI solutions are scalable, reliable, and impactful. This is a hands‑on leadership role, with approximately 70% focused on technical delivery and 30% on team leadership and process optimisation.

What you’ll be doing

• Deliver AI/ML Capabilities
  • Design, build, and deploy scalable AI/ML models, APIs, and LLM‑based solutions (e.g. agents, chatbots)
  • Ensure solutions are secure, reproducible, and aligned with product requirements
  • Drive best practices in model development, evaluation, and deployment
  • Collaborate with product and engineering teams to deliver impactful customer‑facing capabilities
• Lead Agile Delivery
  • Facilitate Scrum ceremonies including stand‑ups, sprint planning, reviews, and retrospectives
  • Drive continuous improvement in team processes and delivery efficiency
  • Ensure realistic planning, accurate estimation, and consistent delivery of sprint goals
  • Promote a culture focused on outcomes over output
• Technical Architecture & Decision Making
  • Own the technical direction and architectural integrity of AI/ML solutions
  • Lead design discussions and ensure alignment with wider engineering strategy
  • Maintain clear documentation and decision logs for architectural choices
  • Enable team autonomy through guidance and governance rather than top‑down control
• Resolve Issues & Handle Production Incidents
  • Investigate and resolve issues across models, data pipelines, and AI systems
  • Lead incident response for production outages, ensuring rapid mitigation and resolution
  • Implement improvements to prevent recurrence and enhance system reliability
• Collaborate with Product & Stakeholders
  • Work closely with Product Managers to refine and prioritise AI/ML initiatives
  • Translate business needs into scalable technical solutions
  • Act as a bridge between technical teams and business stakeholders
• Ensure Quality & Best Practices
  • Conduct code and model reviews to maintain high engineering standards
  • Champion best practices in testing, documentation, and scalability
  • Ensure model performance and outputs are measurable, explainable, and reliable
• Estimate & Plan Work
  • Lead estimation for AI/ML experimentation and delivery
  • Use data‑driven approaches to improve planning accuracy over time
• Keeping Pace with Technology
  • Stay up to date with advancements in AI/ML, LLMs, and engineering practices
  • Evaluate and introduce new tools, frameworks, and methodologies
  • Promote innovation through experimentation and knowledge sharing
• Soft Skills
  • Mentor Members of the Team
    • Coach and support engineers and data scientists at all levels
    • Provide technical guidance, career development support, and constructive feedback
    • Foster a collaborative, high‑performance team environment
    • Support hiring, onboarding, and growth of team members
  • Communication
    • Communicate clearly and effectively across technical and non‑technical stakeholders
    • Share progress, challenges, and insights through demos, updates, and documentation
    • Encourage open feedback and transparent collaboration within the team

  Benefits

  • 25 Days Annual leave, increasing to 26 days after 12 months in the business
  • Enhanced Company Pension (Matched up to 5% & Salary Sacrifice)
  • Healthcare Cashplan with Medicash
  • Private Healthcare with Aviva
  • Life Insurance with AIG
  • Happl, our benefit platform offering pre‑negotiated discounts on a wide variety of services including entertainment, food, and fitness
  • Stock / Equity