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- Tasks: Lead the design and deployment of advanced AI solutions in the energy sector.
- Company: Join Hypercube Consulting, a rapidly growing AI consultancy transforming energy with cutting-edge technology.
- Benefits: Enjoy flexible working, career growth opportunities, and a supportive start-up culture.
- Why this job: Make a real impact on AI-driven energy solutions while shaping the future of technology.
- Qualifications: Expertise in Agentic AI systems, LLMs, and cloud environments like AWS or Azure.
- Other info: Be part of a diverse team committed to innovation and inclusion.
The predicted salary is between 54000 - 84000 Ā£ per year.
Hypercube Consulting is a rapidly growing data and AI consultancy dedicated to transforming the energy sector through cuttingāedge 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. Join our expert team in shaping the future of AIādriven energy solutions.
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.
As an influential hire in a growing organisation, your impact will be substantial, shaping technical strategy, cultivating our AIāfocused culture, and setting delivery standards. You will:
- Engage clients to understand their challenges, designing innovative Agentic AI and LLMādriven solutions.
- Architect and implement robust AI systems, including endātoāend ML/LLM pipelines and autonomous agentic workflows.
- Promote and establish best practices in LLMOps, AI lifecycle management, and cloudānative AI infrastructure.
- Mentor and develop team expertise, positioning Hypercube as a leader in AI engineering excellence.
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 cuttingāedge Agentic AI architectures and LLM frameworks.
- Design, build, and maintain scalable AI and LLMābased pipelines using AWS or Azure services (e.g., SageMaker, Azure ML, Databricks, OpenAI integrations).
- Oversee AI model lifecycles from data preprocessing and prompt engineering through to deployment and continuous monitoring in production environments.
- Coordinate with crossāfunctional teams (data engineers, data scientists, DevOps, stakeholders) to define and deliver clientāfocused AI solutions.
- Communicate complex AI and LLM methodologies clearly to both technical peers and nonātechnical stakeholders.
- Thought leadership & evangelism
- Advocate for best practices in LLMOps and Agentic AI (prompt engineering, evaluation, agent architectures, CI/CD).
- Engage with the AI community through blogs, speaking engagements, and openāsource contributions.
- Support business development through demos, proposals, and technical preāsales activities.
- Foster strong client relationships, advising on AI and LLM strategic directions.
- Mentor colleagues, enhancing the team's collective capabilities.
Technical skills
Please apply even if you meet only some criteria ā we value potential alongside experience.
- Core skills
- Agentic AI & LLMs: Handsāon experience building, deploying, and managing large language models and agentābased AI workflows.
- Cloud AI (AWS/Azure): Demonstrated experience delivering AI solutions in production cloud environments.
- Advanced Python: Expertise in developing efficient, productionāgrade AI/ML code.
- LLMOps & AI Model Management: Experience with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms.
- Data Processing: Proficient with Databricks/Spark for largeāscale AI data processing.
- SQL: Strong capabilities in data querying and preparation.
- Data Architectures: Understanding of modern data infrastructure (lakehouses, data lakes, vector databases).
- Additional (niceātoāhave) skills
- Infrastructure as Code: Terraform or similar.
- Streaming: Kafka, Kinesis, Event Hubs.
- AWS or Azure certifications.
- Consulting or Energy sector.
- Public Thought Leadership (blogs, conferences, open source).
- Effective stakeholder engagement and business requirements translation.
- Integration with complex external or hybrid cloud systems.
- Excellent communication across diverse technical audiences.
What's in it for you?
- High Impact: Drive innovation in energyāsector 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.
- Startāup Culture: Contribute significantly to shaping our culture, processes, and technologies.
- Personal Branding: Encouraged and supported in building your public professional profile.
- Enhanced pension.
- Performance related bonus.
- Enhanced maternity/paternity.
- Cycle to work scheme.
- Events and community participation.
- Private health insurance.
- Health cash plan.
- EV leasing scheme.
- Training and events budget.
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 ā even if you meet some but not all criteria. We're excited to explore how your expertise can help transform data and AI in the energy sector!
N.B. We are currently not able to sponsor visas.
Principal AI Engineer in London employer: Hypercube
Contact Detail:
Hypercube Recruiting Team
StudySmarter Expert Advice š¤«
We think this is how you could land Principal AI Engineer in London
āØTip Number 1
Network like a pro! Get out there and connect with folks in the AI and energy sectors. Attend meetups, webinars, or industry events. You never know who might be looking for someone just like you!
āØTip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Agentic AI and LLMs. Share it on platforms like GitHub or even your own website to grab attention.
āØTip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex AI concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
āØTip Number 4
Don't forget to apply through our website! Itās the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to shape the future of AI in the energy sector.
We think you need these skills to ace Principal AI Engineer in London
Some tips for your application š«”
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and its potential in the energy sector shine through. We love seeing candidates who are genuinely excited about the technology and how it can transform industries.
Tailor Your Experience: Make sure to highlight your relevant experience with Agentic AI systems and LLMs. We want to see how your skills align with our needs, so donāt be shy about showcasing your past projects and achievements that relate to the role.
Be Clear and Concise: While we appreciate detail, clarity is key! Use straightforward language to explain your technical expertise and how it applies to the role. Remember, we want to understand your thought process without getting lost in jargon.
Apply Through Our Website: We encourage you to apply directly through our careers page. Itās the best way for us to receive your application and ensures youāre considered for the role. Plus, it shows youāre keen on joining our team!
How to prepare for a job interview at Hypercube
āØKnow Your AI Stuff
Make sure you brush up on your knowledge of Agentic AI systems 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.
āØShowcase Your Cloud Skills
Since the role involves working with AWS or Azure, be prepared to talk about your experience with these platforms. Highlight any specific tools you've used, like SageMaker or Azure ML, and explain how you've implemented AI solutions in cloud environments. Real-world examples will make your case stronger!
āØCommunicate Clearly
You'll need to explain complex AI methodologies to both technical and non-technical audiences. Practice articulating your thoughts clearly and concisely. Consider using analogies or simple terms to break down complicated ideas, as this will demonstrate your ability to engage with diverse stakeholders.
āØBe a Team Player
Collaboration is key in this role, so be ready to discuss how you've worked with cross-functional teams in the past. Share examples of how youāve coordinated with data engineers, data scientists, and other stakeholders to deliver successful AI solutions. This will highlight your leadership potential and teamwork skills.
