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- Tasks: Lead the design and deployment of advanced AI solutions in a collaborative environment.
- Company: Join Hypercube Consulting, a fast-growing tech consultancy transforming the energy sector with AI.
- Benefits: Enjoy flexible working arrangements, performance bonuses, and a supportive mentorship programme.
- Why this job: Make a significant impact on AI-driven energy solutions while shaping company culture and strategy.
- Qualifications: Experience with Agentic AI, LLMs, and cloud platforms like AWS or Azure is essential.
- Other info: Diversity and inclusion are key; we welcome applicants from all backgrounds.
The predicted salary is between 68000 - 85000 £ per year.
Compensation: £80,000 – £100,000 base salary + performance-related bonus + benefits
Role: Principal AI Engineer (Agentic AI & LLM Specialist)
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 (unless preferred)
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 consultancy 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 a Principal AI Engineer with expertise in Agentic AI systems and Large Language Models to lead the design, development, and deployment of advanced AI solutions. You will collaborate closely with data engineering, analytics, and cloud teams to deliver transformative AI capabilities for our clients.
Key Responsibilities:
- Technical Leadership & Strategy: Act as the AI and LLM subject matter expert for internal teams and client engagements. Drive the strategic design and implementation of sophisticated AI solutions leveraging cutting-edge Agentic AI architectures and LLM frameworks.
- End-to-End AI Delivery: Design, build, and maintain scalable AI and LLM-based pipelines using AWS or Azure services. Oversee AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production environments.
- Collaboration & Stakeholder Management: Coordinate with cross-functional teams to define and deliver client-focused AI solutions. Communicate complex AI and LLM methodologies clearly to both technical peers and non-technical stakeholders.
- Thought Leadership & Evangelism: Advocate for best practices in LLMOps and Agentic AI. Engage with the AI community through blogs, speaking engagements, and open-source contributions.
- Business Development & Growth: Support business development through demos, proposals, and technical pre-sales activities. Foster strong client relationships, advising on AI and LLM strategic directions.
Technical Skills & Experience:
- Core Skills: Hands-on experience building, deploying, and managing large language models and agent-based AI workflows. Demonstrated experience delivering AI solutions in production cloud environments. Expertise in developing efficient, production-grade AI/ML code.
- Additional (Nice-to-Have) Skills: Infrastructure as Code, Containers & Kubernetes, Streaming, AWS or Azure certifications.
Desirable Experience: Consulting or Energy sector experience. Public Thought Leadership. Effective stakeholder engagement and business requirements translation.
What’s in It for You?
- High Impact: Drive innovation in energy-sector AI solutions, directly influencing client outcomes.
- Career Growth: Benefit from senior mentorship, dedicated training budgets, and clear growth pathways.
- Flexible Environment: Open to various flexible working arrangements to suit your lifestyle.
- Start-up Culture: Contribute significantly 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.
Diversity & Inclusion: Hypercube is committed to creating an inclusive environment reflective of society. We actively encourage applications from all backgrounds and experiences.
Ready to Apply? If this role excites you, please apply via our careers page or reach out directly—even if you meet some but not all criteria.
Principal AI Engineer employer: Hypercube Consulting
Contact Detail:
Hypercube Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in Agentic AI and large language models. Engage with online communities, attend webinars, or follow thought leaders in the field to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the role.
✨Tip Number 2
Network with professionals in the energy sector and AI consultancy. Attend industry events or join relevant online forums to connect with potential colleagues or mentors. Building these relationships can provide valuable insights and may even lead to referrals for the position.
✨Tip Number 3
Prepare to discuss your experience with cloud platforms like AWS or Azure in detail. Be ready to share specific examples of projects where you've implemented AI solutions in production environments. This will showcase your technical expertise and align with the job requirements.
✨Tip Number 4
Demonstrate your ability to communicate complex AI concepts to non-technical stakeholders. Practice explaining your past projects in simple terms, as this skill is crucial for the role. Highlighting this ability can set you apart from other candidates.
We think you need these skills to ace Principal AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Agentic AI and large language models. Include specific projects or roles where you've implemented these technologies, especially in cloud environments like AWS or Azure.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and the energy sector. Mention how your skills align with the role's requirements and how you can contribute to Hypercube Consulting's mission of transforming the energy sector through AI.
Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or a brief description of these projects in your application. Highlight your role, the technologies used, and the impact of your work.
Highlight Soft Skills: Since the role involves collaboration and stakeholder management, emphasise your communication skills and ability to work in cross-functional teams. Provide examples of how you've successfully engaged with both technical and non-technical stakeholders.
How to prepare for a job interview at Hypercube Consulting
✨Showcase Your AI Expertise
Be prepared to discuss your hands-on experience with Agentic AI systems and large language models. Highlight specific projects where you've designed, developed, or deployed AI solutions, and be ready to explain the impact of your work.
✨Demonstrate Cloud Proficiency
Since the role requires cloud experience, ensure you can articulate your familiarity with AWS or Azure. Discuss any relevant certifications you hold and provide examples of how you've used these platforms to deliver AI solutions in production environments.
✨Communicate Clearly with Stakeholders
Practice explaining complex AI concepts in simple terms. You'll need to engage with both technical peers and non-technical stakeholders, so being able to bridge that gap will be crucial during your interview.
✨Emphasise Collaboration Skills
The role involves coordinating with cross-functional teams, so share examples of how you've successfully collaborated with data engineers, data scientists, and other stakeholders. Highlight your ability to foster strong relationships and drive client-focused solutions.
