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£80,000 – £100,000 base salary + performance-related bonus + benefits

Performance-Related Bonus

Great benefits (listed below)

TL;DR

• 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. Join our expert team in shaping the future of AI-driven energy solutions.

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.

As an influential hire in a growing organisation, your impact will be substantial, shaping technical strategy, cultivating our AI-focused culture, and setting delivery standards. You will:

• Engage clients to understand their challenges, designing innovative Agentic AI and LLM-driven solutions.
• Architect and implement robust AI systems, including end-to-end ML/LLM pipelines and autonomous agentic workflows.
• Promote and establish best practices in LLMOps, AI lifecycle management, and cloud-native 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 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 (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.

Collaboration & Stakeholder Management

• Coordinate with cross-functional teams (data engineers, data scientists, DevOps, stakeholders) 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 (prompt engineering, evaluation, agent architectures, CI/CD).
• 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.
• Mentor colleagues, enhancing the team's collective capabilities.

Technical Skills & Experience

Please apply even if you meet only some criteria—we value potential alongside experience.

Core Skills

• Agentic AI & LLMs: Hands-on experience building, deploying, and managing large language models and agent-based AI workflows.
• Cloud AI (AWS/Azure): Demonstrated experience delivering AI solutions in production cloud environments.
• Advanced Python: Expertise in developing efficient, production-grade 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 large-scale AI data processing.
• SQL: Strong capabilities in data querying and preparation.
• Data Architectures: Understanding of modern data infrastructure (lakehouses, data lakes, vector databases).

Additional (Nice-to-Have) Skills

• Infrastructure as Code: Terraform or similar.
• Streaming: Kafka, Kinesis, Event Hubs.
• AWS or Azure certifications.
• Consulting or Energy sector experience.
• 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 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.
• Performance-Related Bonus
• Enhanced Pension
• Enhanced Maternity/Paternity
• Private Health Insurance
• Health Cash Plan
• Cycle-to-Work Scheme
• Flexible Remote/Hybrid Working
• Events & Community Participation
• EV Leasing Scheme
• Training & 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—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. Visa sponsorship is currently not available.