At a Glance
- Tasks: Design and deliver AI-driven tools for energy trading, transforming complex data into actionable insights.
- Company: Join Aubay UK, a leading digital services company in the energy sector.
- Benefits: Enjoy 25 days annual leave, remote work options, and a competitive salary.
- Other info: Collaborative environment with excellent career development opportunities.
- Why this job: Make a real impact in energy trading with cutting-edge AI technology.
- Qualifications: Strong experience in applied AI, Python proficiency, and data engineering skills required.
The predicted salary is between 60000 - 80000 £ per year.
Aubay UK is seeking an Applied AI Engineer – Decision Support (Energy Trading) to join a permanent engagement based in London. This role focuses on designing and delivering AI-driven decision-support tools for energy trading, with an emphasis on transforming complex market, pricing, and internal analytics data into clear, thesis-driven insights. The successful candidate will work on a trading use case, building scalable, explainable AI systems that support traders’ decision-making without automated execution, while meeting strict security, compliance, and governance standards.
Required Skills and Experience
- Strong experience building applied AI or machine learning systems in production environments
- Proficiency in Python for data processing, model integration, and orchestration
- Experience deploying services on Kubernetes-based infrastructure
- Solid understanding of data engineering concepts, including data quality, freshness, and monitoring
- Experience integrating multiple data sources (public and proprietary) into coherent analytical workflows
- Ability to design explainable, transparent AI outputs suitable for decision support
- Strong communication skills and ability to work closely with traders and subject matter experts
Desired Skills and Experience
- Experience in commodities, energy trading, or financial markets
- Familiarity with live pricing feeds and market data systems
- Experience implementing human-in-the-loop or feedback-driven learning systems
- Knowledge of evaluation frameworks for model robustness, sensitivity, and consistency
- Experience working in regulated or security-conscious enterprise environments
Role Responsibilities
- Design and implement AI-driven decision-support components for energy trading use cases
- Integrate public market data with proprietary internal analytics and live pricing inputs
- Develop thesis-first reasoning frameworks that generate trade ideas with evidence, risks, and counter-arguments
- Implement feedback loops to capture trader ratings and comments for iterative improvement
- Build and maintain evaluation tooling for sensitivity, robustness, and consistency testing
- Ensure solutions meet security, compliance, and data-handling standards
- Collaborate closely with traders, data scientists, and platform engineers to iterate on usability and quality
Client Description
Our client is a global energy trading and analytics organisation operating across physical and financial commodity markets. The organisation leverages advanced analytics, data science, and digital platforms to support trading decision-making across distillates and other energy products, with a strong focus on security, governance, and scalable cloud-native infrastructure.
About Aubay
Aubay UK is a recognised InSourcing Partner for client-side deployment delivered across London. Our team, based in Canary Wharf, specialises in hiring IT professionals within London’s Energy and FinTech sectors, helping our clients to expand their operations with top-tier talent who are experts in their fields. We work exclusively with clients who are globally recognized as Energy Super Majors/Financial Services and innovative FinTech players.
Aubay UK is proud to be an equal opportunity employer. All aspects of employment decisions will be based on merit, competence, performance, and business needs.
- 25 Days Annual Leave
- Work From Home Opportunities
- Pension Scheme
- Opportunities to Work Directly with our Client
- Training Opportunities
- Discount Holidays at I’Aero Chalet
Applied AI Engineer – Decision Support (Energy Trading) in Slough employer: Aubay
Aubay UK is an exceptional employer, offering a dynamic work environment in the heart of London with a hybrid working model that promotes work-life balance. Employees benefit from a competitive remuneration package, extensive training opportunities, and the chance to collaborate with leading experts in the energy trading sector, all while contributing to innovative AI-driven solutions that shape the future of decision-making in this critical industry.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer – Decision Support (Energy Trading) in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the energy trading and AI space on LinkedIn. Join relevant groups, attend webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to decision support or energy trading. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Research common questions for AI Engineer roles and practice your responses. Be ready to discuss your experience with Python, Kubernetes, and data integration, as well as how you can contribute to their team.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly shows your enthusiasm and makes it easier for us to connect you with the right role.
We think you need these skills to ace Applied AI Engineer – Decision Support (Energy Trading) in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Applied AI Engineer role. Highlight your experience with AI systems, Python, and any relevant projects that showcase your skills in energy trading or decision support.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're the perfect fit for this role. Share your passion for AI and energy trading, and explain how your background aligns with the responsibilities outlined in the job description.
Showcase Your Communication Skills:Since you'll be working closely with traders and data scientists, it's important to demonstrate your strong communication skills. Use clear and concise language in your application to show us you can convey complex ideas effectively.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. This way, we can easily track your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Aubay
✨Know Your AI Stuff
Make sure you brush up on your applied AI and machine learning knowledge. Be ready to discuss your experience building systems in production environments, especially using Python. They’ll want to hear about specific projects where you’ve integrated data sources and designed explainable AI outputs.
✨Understand the Energy Trading Landscape
Familiarise yourself with the energy trading sector, particularly commodities and financial markets. Knowing how live pricing feeds work and the importance of data quality will give you an edge. It’s all about showing that you can translate complex data into actionable insights for traders.
✨Show Off Your Collaboration Skills
This role involves working closely with traders and data scientists, so be prepared to share examples of how you’ve successfully collaborated in the past. Highlight your communication skills and any experience you have with feedback-driven learning systems, as they’re key to improving decision support tools.
✨Prepare for Technical Questions
Expect some technical questions around deploying services on Kubernetes and ensuring compliance with security standards. Brush up on evaluation frameworks for model robustness and be ready to discuss how you would handle data integration challenges. Confidence in these areas will show you’re the right fit for the role.
