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For Companies At a Glance
- Tasks: Design and develop innovative AI solutions in a collaborative environment.
- Company: Hypercube Consulting is a cutting-edge consultancy transforming the energy sector with AI.
- Benefits: Enjoy flexible working, performance bonuses, and a supportive mentorship programme.
- Why this job: Join a dynamic team to shape the future of AI while making a real impact.
- Qualifications: Experience with Agentic AI, LLMs, and cloud platforms like AWS or Azure is essential.
- Other info: Diversity is key; we welcome applicants from all backgrounds.
The predicted salary is between 50000 - 70000 £ per year.
Compensation £60,000 – £80,000 base salary + performance-related bonus + benefits
Location: UK-based, fast-growing technology consultancy specialising in the energy sector
Cloud Experience: Must have AWS or Azure (certifications desirable)
Management: No direct line management required
Consultancy/Energy Experience: Beneficial, but not 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—we encourage applicants from all backgrounds
Who We Are
Hypercube Consulting is an innovative data and AI consultancy dedicated to revolutionising the energy sector. We specialise in advanced Agentic AI workflows and Large Language Models (LLMs), empowering our clients to realise significant value from their data.
Role Purpose
We are looking for a Senior AI Engineer with experience in Agentic AI and LLM technologies to design and develop impactful AI solutions. You will work alongside data engineers, data scientists, and cloud specialists, directly contributing to client success.
In this role, you will:
- Engage with client challenges, developing practical and innovative Agentic AI and LLM solutions.
- Implement and optimise AI workflows and model pipelines.
- Promote good practice in AI lifecycle management and cloud-native infrastructure.
- Collaborate closely with experienced team members, contributing to Hypercube’s growing AI expertise.
Key Responsibilities
Technical Contribution
- Develop and deploy reliable AI and LLM solutions, collaborating with senior team members.
- Contribute to the implementation and maintenance of AI pipelines (data ingestion, model training, deployment, and monitoring).
Collaboration & Communication
- Work within multidisciplinary teams to deliver client-focused solutions.
- Effectively communicate AI concepts and methodologies to peers and clients.
Continuous Learning & Development
- Stay up-to-date with developments in Agentic AI, LLMs, and AI best practices.
- Support internal knowledge sharing and mentorship activities.
Technical Skills & Experience
Core Skills
- Agentic AI & LLMs: Practical experience deploying and managing large language models and agent-based workflows.
- Cloud AI (AWS/Azure): Experience deploying AI solutions on cloud platforms.
- Python: Proficient in writing clean, production-quality code.
- AI Model Management: Familiarity with platforms such as MLFlow, Hugging Face, or LangChain.
- Data Processing: Experience with Databricks/Spark.
- SQL: Solid querying and data preparation skills.
- Data Architectures: Understanding of modern data systems (lakehouses, data lakes).
Additional (Nice-to-Have) Skills
- Infrastructure as Code: Terraform or equivalent.
- Containers & Kubernetes: Docker, Kubernetes.
- Streaming: Kafka, Kinesis.
- Cloud certifications (AWS or Azure).
Desirable Experience
- Experience in consulting or the energy sector.
- Public engagement through blogging or speaking.
- Strong communication and stakeholder engagement.
- Integration with hybrid or external systems.
What’s in It for You?
- Impactful Work: Contribute to innovative AI solutions within the energy sector.
- Career Development: Learn from senior experts and benefit from tailored training.
- Flexible Working: Accommodate your personal and professional lifestyle.
- Start-Up Atmosphere: Help shape our culture and processes.
- Personal Branding: Support in developing 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
Diversity & Inclusion
Hypercube is committed to a diverse, inclusive workplace. Applications from all backgrounds and experiences are warmly encouraged.
Ready to Apply?
If this role excites you, please apply via our careers page or contact us directly—even if you meet only some criteria. We’re eager to explore how your talents can help drive AI innovation in the energy sector.
Senior AI Engineer employer: Hypercube Consulting
Contact Detail:
Hypercube Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in Agentic AI and LLM technologies. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your cloud experience, particularly with AWS or Azure. If you have any relevant certifications, be sure to mention them, as they can significantly boost your credibility.
✨Tip Number 3
Network with professionals in the energy sector and AI community. Attend meetups or webinars to connect with potential colleagues and learn more about the challenges they face, which can give you an edge in interviews.
✨Tip Number 4
Prepare to discuss your experience with AI model management tools like MLFlow or Hugging Face. Being able to articulate your hands-on experience with these platforms will demonstrate your technical expertise.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Agentic AI and LLM technologies. Emphasise any cloud experience, particularly with AWS or Azure, and showcase your technical skills in Python and AI model management.
Craft a Compelling Cover Letter: Write a cover letter that connects your background to the role. Discuss your passion for AI in the energy sector and how your skills can contribute to Hypercube's mission. Mention any consulting experience or public engagement that aligns with their values.
Showcase Continuous Learning: In your application, highlight any recent courses, certifications, or projects related to AI, LLMs, or cloud technologies. This demonstrates your commitment to staying updated in a fast-evolving field.
Prepare for Technical Questions: Anticipate technical questions related to AI workflows, model pipelines, and cloud infrastructure during the interview process. Be ready to discuss specific projects where you implemented these technologies.
How to prepare for a job interview at Hypercube Consulting
✨Showcase Your AI Expertise
Be prepared to discuss your experience with Agentic AI and LLM technologies in detail. Highlight specific projects where you've deployed these solutions, focusing on the impact they had on client outcomes.
✨Demonstrate Cloud Proficiency
Since cloud experience is crucial, ensure you can talk about your work with AWS or Azure. If you have certifications, mention them, and be ready to explain how you've used these platforms to deploy AI solutions.
✨Communicate Clearly
Effective communication is key in consultancy roles. Practice explaining complex AI concepts in simple terms, as you'll need to convey these ideas to clients and team members who may not have a technical background.
✨Emphasise Continuous Learning
Show your commitment to staying updated with the latest developments in AI. Discuss any recent courses, workshops, or conferences you've attended, and how you plan to apply this knowledge in your role.
