At a Glance
- Tasks: Lead a team to design and deploy innovative AI/ML solutions that transform global supply chains.
- Company: Join RedCloud, a pioneering tech firm revolutionising global trade with AI.
- Benefits: Enjoy 25 days annual leave, enhanced pension, private healthcare, and stock options.
- Other info: Dynamic, diverse team with opportunities for growth and innovation.
- Why this job: Make a real impact on global trade while leading cutting-edge AI projects.
- Qualifications: Proven experience in AI/ML and strong leadership skills required.
The predicted salary is between 80000 - 98000 £ per year.
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
Lead AI Engineer employer: RedCloud
RedCloud is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. With a strong focus on employee growth, we provide extensive benefits including enhanced pension plans, private healthcare, and generous annual leave, fostering a culture that values accountability and continuous improvement. Join us to lead cutting-edge AI initiatives while being part of a diverse team dedicated to transforming global supply chains and making a meaningful impact.
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We think this is how you could land Lead AI Engineer
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We think you need these skills to ace Lead AI Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RedCloud. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RedCloud
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
