GenAI Engineer: From Prototyping to Production in Energy

Vallum Associates; Exeter; On-site; GBP 111,000 - 166,000; Full time

Job summary

Vallum Associates seeks an experienced AI / GenAI Engineer to design, build and prototype practical AI solutions within a leading UK energy services environment. The role is hands-on, focusing on turning ideas into working PoCs and production-ready solutions for the Service Management function.

Based in Exeter with two days on site, you will collaborate with engineering, data, security and business stakeholders to deliver secure, scalable AI capabilities using LLMs, embeddings and RAG, across

Qualifications

• Hands-on AI / GenAI engineering experience.
• Prototyping AI apps, prototypes and PoCs.
• Strong Python development skills.
• Practical experience with LLMs and LLM APIs.
• Experience with RAG, embeddings and vector databases.
• Experience building AI agents / agentic workflows is desirable.

Responsibilities

• Design and build AI and GenAI solutions for Service Management use cases.
• Develop working prototypes and Proofs of Concept.
• Build solutions using LLMs, APIs, RAG, agents and automation technologies.
• Integrate AI capabilities with existing enterprise systems and data.
• Evaluate models and approaches for different use cases.
• Take concepts through design, build and testing to production.

Skills

Hands-on AI engineering

Prototyping & PoC development

Python development

LLMs & APIs

Prompt engineering

Cloud AI (AWS/Azure/GCP)

Tools

LLMs & APIs

RAG / embeddings

Vector databases

Agentic workflows

Job description

Vallum Associates seeks an experienced AI / GenAI Engineer to design, build and prototype practical AI solutions within a leading UK energy services environment. The role is hands-on, focusing on turning ideas into working PoCs and production-ready solutions for the Service Management function.

Based in Exeter with two days on site, you will collaborate with engineering, data, security and business stakeholders to deliver secure, scalable AI capabilities using LLMs, embeddings and RAG, across