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- Tasks: Design and develop advanced AI solutions for the energy sector using cutting-edge technology.
- Company: Join a fast-growing tech startup transforming the energy industry with innovative AI.
- Benefits: Enjoy a competitive salary, performance bonuses, flexible working, and great health benefits.
- Other info: Be part of a diverse team committed to inclusion and personal growth.
- Why this job: Make a real impact in AI-driven energy solutions while growing your career.
- Qualifications: Experience with Agentic AI, LLMs, and cloud platforms like AWS or Azure.
The predicted salary is between 40000 - 70000 £ per year.
Compensation: £40,000 – £70,000 base salary + performance-related bonus + benefits.
Location: UK-based, fast-growing technology startup specialising in the energy sector.
Cloud Experience: Must have AWS or Azure (certifications desirable).
Management: No direct line management required.
Consultancy/Energy Experience: Highly beneficial, non-essential.
Visa Sponsorship: Not currently available; right to work and UK residency required.
Flexibility: Part-time, condensed hours, job-shares, and flexible arrangements considered.
Diversity & Inclusion: Extremely important—encouraging a broad mix of people from all backgrounds.
Who We Are: Hypercube Consulting is a rapidly growing data and AI startup dedicated to transforming the energy sector through cutting-edge technology. Specialising in advanced AI systems, including Agentic AI workflows and large language models (LLMs), we help clients unlock profound value from their data assets.
Role Purpose: We are seeking an AI Engineer with hands-on experience in Agentic AI systems and Large Language Models to help design, develop, and deploy advanced AI solutions for our clients. You will collaborate closely with data engineering, analytics, and cloud teams to deliver transformative AI capabilities.
Key Responsibilities:
- Technical Delivery: Act as a hands-on AI and LLM practitioner across client engagements and internal projects.
- End-to-End AI Delivery: Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services.
- Collaboration & Stakeholder Management: Work with cross-functional teams to deliver client-focused AI solutions.
- Knowledge Sharing: Apply and help refine best practices in LLMOps and Agentic AI.
- Business Development & Growth: Support business development through demos, proof-of-concept work, and technical pre-sales activities.
Technical Skills & Experience:
- Core Skills:
- Agentic AI & LLMs: Hands-on experience building and deploying large language models and agent-based AI workflows.
- Cloud AI (AWS/Azure): Experience delivering AI or ML solutions in production cloud environments.
- Python: Strong capability in developing production-quality AI/ML code.
- LLMOps & AI Model Management: Familiarity with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms.
- Data Processing: Working knowledge of Databricks/Spark or comparable large-scale data processing tools.
- SQL: Solid capabilities in data querying and preparation.
- Data Architectures: Understanding of modern data infrastructure.
- Infrastructure as Code: Terraform or similar.
- Containers & Kubernetes: Docker, EKS/AKS.
- Streaming: Kafka, Kinesis, Event Hubs.
- AWS or Azure certifications.
Desirable Experience:
- Consulting or Energy sector experience.
- Public profile (blogs, conferences, open source).
- Stakeholder engagement and requirements translation.
- Integration with external or hybrid cloud systems.
- Clear communication across diverse technical audiences.
What's in It for You?
- High Impact: Work on energy-sector AI solutions that directly influence client outcomes.
- Career Growth: Senior mentorship, dedicated training budgets, and a clear pathway to Principal.
- Flexible Environment: Open to various flexible working arrangements to suit your lifestyle.
- Start-up Culture: Contribute to shaping our culture, processes, and technologies.
- Personal Branding: Encouraged and supported in building your public professional profile.
Benefits:
- Performance-Related Bonus
- Enhanced Pension
- Enhanced Maternity/Paternity
- Private Health Insurance
- Health Cash Plan
- Peer Cash Award Scheme
- Cycle-to-Work Scheme
- Flexible Remote/Hybrid Working
- Events & Community Participation
- EV Leasing Scheme
- Training & Events Budget
- Mentorship Programmes
Hypercube is committed to creating an inclusive environment reflective of society. We actively encourage applications from all backgrounds and experiences.
If this role excites you, please apply via our careers page or reach out directly—even if you meet some but not all criteria.
AI Engineer in Glasgow employer: Hypercube Consulting
Contact Detail:
Hypercube Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Agentic AI and LLMs. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common AI concepts and frameworks. Be ready to discuss your previous work and how it relates to the role. Practising with friends or using mock interview platforms can really help!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are excited about transforming the energy sector with AI.
We think you need these skills to ace AI Engineer in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with Agentic AI and LLMs, and don’t forget to mention any cloud experience you have with AWS or Azure. We want to see how your skills match 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 you can contribute to our mission in the energy sector. Keep it engaging and personal—let us know what excites you about this opportunity!
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, we love seeing practical examples of your work with AI systems and cloud technologies.
Apply Through Our Website: We encourage you to apply directly through our careers page. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're genuinely interested in joining our team at Hypercube Consulting!
How to prepare for a job interview at Hypercube Consulting
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Agentic AI and large language models. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show that you're not just familiar with the concepts but have practical experience too.
✨Cloud Experience is Key
Since the role requires AWS or Azure experience, be prepared to talk about your hands-on work with these platforms. Highlight any certifications you have and share examples of how you've used cloud services to deliver AI solutions. This will demonstrate your technical capability and readiness for the role.
✨Collaboration is Crucial
This position involves working closely with cross-functional teams, so be ready to discuss your experience in collaborative environments. Share examples of how you've effectively communicated complex AI concepts to both technical and non-technical stakeholders. This will show that you can bridge the gap between different teams.
✨Show Your Passion for AI
Engage with the AI community by mentioning any blogs, speaking engagements, or open-source contributions you've made. This not only showcases your expertise but also your enthusiasm for the field. Companies love candidates who are passionate about their work and actively contribute to the community.