At a Glance
- Tasks: Design and deploy advanced AI solutions for a leading energy client.
- Company: Join a Super Major global energy company focused on cleaner energy solutions.
- Benefits: Competitive salary, career development support, and a dynamic work environment.
- Other info: Collaborate with multidisciplinary teams and lead innovative AI projects.
- Why this job: Make a real impact in transforming energy business towards net-zero emissions by 2050.
- Qualifications: 5+ years in AI/ML, strong Python skills, and a relevant STEM degree.
The predicted salary is between 60000 - 80000 £ per year.
Aubay UK is seeking a highly skilled and versatile Senior AI Engineer for our leading oil and gas client. The Senior AI Engineer is responsible for designing, developing, and deploying advanced AI and machine-learning solutions for enterprise-level clients. The ideal candidate will have a strong foundation in mathematics or computer science and a proven track record of delivering innovative AI capabilities across diverse industries. This role requires both strategic and hands-on technical expertise, with the ability to operate autonomously, evaluate trade-offs, recommend optimal approaches, and own the end-to-end development of impactful AI solutions.
The engineer will work collaboratively across multidisciplinary teams, providing thought leadership in cutting-edge AI technologies, including deep learning, graph neural networks, generative AI, and retrieval augmented systems.
- 5+ years of professional experience delivering advanced AI / ML solutions in industry or engineering environments.
- Strong expertise in Python and AI/ML libraries.
- Proven hands-on experience deploying models in production and building scalable AI software.
- Deep understanding of advanced modelling methods: deep learning, GNNs, computer vision, sensor fusion, vector embeddings, RAG, generative AI.
- Experience designing AI/ML architectures and providing strategic technical guidance to enterprise clients.
- Proficiency with cloud compute platforms for training and deployment (Azure, AWS, GCP, or similar).
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or related STEM field.
- Background in reliability engineering, corrosion, WRFM (Well & Reservoir Facility Management), advanced sensing, or process engineering.
- Hands-on experience with platforms such as Azure ML Studio, Palantir Foundry, or Databricks Mosaic.
- Familiarity with NLP, LLM deployment, agent-based AI (MCP, A2A, N8N), and advanced RAG architectures.
Lead the end-to-end development, deployment, and delivery of AI and machine learning solutions for enterprise clients, ensuring scalability, reliability, and real-world impact. Apply advanced AI techniques—including deep learning, classical ML, graph neural networks, object detection, sensor fusion, vector embeddings, retrieval-augmented generation (RAG), and generative AI models—to design systems that learn, adapt, and operate autonomously.
Provide strategic architectural guidance on AI systems, ensuring efficient design, cloud-ready deployment, and alignment with enterprise architectural standards. Collaborate with multidisciplinary teams (engineering, product, domain experts) to create AI-driven solutions that automate analysis, enhance decision-making, and generate actionable insights.
Lead the design and implementation of AI pipelines, including experimentation, model training, evaluation, optimisation, and production deployment. Serve as a thought leader on emerging AI technologies, including LLMs, generative AI, agent-based systems (MCP, A2A, N8N), and advanced RAG frameworks, helping guide innovation and best practices.
Ensure all AI solutions meet standards for performance, security, cloud governance, and operational reliability, leveraging modern cloud environments for model training and deployment.
Our client is one of the Super Major global energy companies working to power progress through cleaner energy solutions. You will have the opportunity to work in a challenging but rewarding environment that is fast-paced and changing fundamentally, and work towards transforming the business of a Super Major energy company to meet the ambition to be a net-zero emissions energy business by 2050, whilst delivering a world-class business case that has a strong societal license to operate. You will receive continuous support from our dedicated team of Talent Acquisition Specialists who will support your career development and success during your assignment with our client.
Remote AI Engineer employer: Aubay UK
Aubay UK is an exceptional employer, offering a dynamic work environment where innovation thrives and employees are empowered to lead the development of cutting-edge AI solutions for a leading global energy client. With a strong focus on professional growth, our collaborative culture fosters continuous learning and provides ample opportunities to engage with advanced technologies while contributing to the ambitious goal of achieving net-zero emissions by 2050. Join us to be part of a transformative journey in the energy sector, supported by a dedicated team committed to your success.
StudySmarter Expert Advice🤫
We think this is how you could land Remote AI Engineer
✨Tip Number 1
Network like a pro! Reach out to industry professionals on LinkedIn or attend virtual meetups. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects and solutions. This gives potential employers a taste of what you can do, and we all know actions speak louder than words.
✨Tip Number 3
Prepare for interviews by brushing up on common AI-related questions and case studies. We recommend practising with friends or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re here to support you every step of the way in landing that dream job.
We think you need these skills to ace Remote AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior AI Engineer. Highlight your experience with AI/ML solutions and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a perfect fit for this role. We love seeing enthusiasm and a personal touch!
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise, especially in Python and AI/ML libraries. Mention any hands-on experience with cloud platforms like Azure or AWS, as this is crucial for the role. We need to know you can hit the ground running!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates. Plus, it’s super easy!
How to prepare for a job interview at Aubay UK
✨Know Your AI Stuff
Make sure you brush up on your knowledge of advanced AI techniques like deep learning, graph neural networks, and generative AI. Be ready to discuss specific projects where you've applied these methods, as well as the challenges you faced and how you overcame them.
✨Showcase Your Hands-On Experience
Prepare to talk about your hands-on experience with Python and AI/ML libraries. Highlight any models you've deployed in production and the impact they had. If you've worked with cloud platforms like Azure or AWS, be sure to mention that too!
✨Collaboration is Key
Since this role involves working with multidisciplinary teams, think of examples where you've successfully collaborated with others. Discuss how you contributed to team projects and how you ensured everyone was aligned towards a common goal.
✨Be Ready for Technical Questions
Expect some technical questions during the interview. Brush up on AI/ML architectures and be prepared to explain your thought process when designing systems. They might ask you to evaluate trade-offs or recommend optimal approaches, so think critically about your past experiences.
