Job Title: Senior AI Solutions Engineer

Location: UK – Hybrid with on-site responsibilities

Department: Product & Strategy

Reports To: VP, Product & Strategy

Employment Type: Full-time

About the Company

A fast-growing UK-based AI infrastructure and solutions provider is delivering next-generation enterprise AI capabilities with a strong emphasis on sustainability, data sovereignty, and real-world outcomes. Backed by significant investment and strategic partnerships, the company operates a national AI infrastructure platform that spans 50+ datacenter locations and is powered entirely by renewable energy.

The mission is to help enterprises operationalise AI faster, more efficiently, and with full control over their data — offering a complete platform that combines infrastructure, software, and services.

About the Role

This is a strategic, customer-facing engineering role where you’ll design and deliver complex AI solutions using retrieval-augmented generation (RAG), LLM fine-tuning, and enterprise-grade inference deployment. You’ll work closely with commercial teams, product, and platform engineering to bring cutting-edge AI solutions to life for enterprise clients — all while working within a sovereign, sustainable AI mesh.

Key Responsibilities

Customer Solution Design

• Collaborate with enterprise customers to map business problems to AI-powered workflows.
• Architect full-stack solutions using RAG, fine-tuning, and scalable inference endpoints.
• Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams.

AI & ML Engineering

• Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton.
• Fine-tune foundation models for domain-specific use cases.
• Deploy and maintain inference services using REST/gRPC APIs, containerised and distributed systems.

Data & Knowledge Integration

• Build secure, scalable data pipelines that integrate enterprise data into vector stores and embedding models.
• Optimise semantic retrieval for performance and relevance in generative AI applications.

Cross-Team Collaboration

• Work with infrastructure and platform engineering teams to ensure smooth deployments.
• Feed insights back into the product team to shape platform features.
• Mentor junior engineers and contribute to customer enablement content.

Sample Success Metrics

• Deliver 5+ enterprise AI deployments (RAG, fine-tuned models, inference endpoints).
• Contribute to solution accelerators (code repos, templates, tools) used across projects.
• Help drive measurable revenue through technical pre-sales and solution support.
• Maintain high client satisfaction scores post-deployment.
• Produce thought leadership (blogs, talks, case studies) on real-world AI implementation.

Required Qualifications

• Background in AI/ML engineering, applied AI, or technical solutions delivery.
• Strong experience with:
• Retrieval-Augmented Generation (e.g., LangChain, LlamaIndex, vector databases).
• LLM fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Deploying models in production (Triton Inference Server, HuggingFace, Kubernetes).
• Advanced Python skills; bonus for experience in Go, Java, or C++.
• Direct experience working with enterprise clients.
• Solid understanding of embeddings, vector stores, and semantic search.

Preferred Qualifications

• Familiarity with enterprise AI stacks (e.g., NVIDIA AI Enterprise, private cloud AI platforms).
• Awareness of UK AI compliance and data sovereignty regulations (e.g., ISO 27001, SOC 2).
• Experience optimising GPU workloads.
• Contributions to open-source AI/ML projects or toolkits.

Compensation & Benefits

• Competitive salary
• Potential equity or performance-based incentives
• Learning and development budget
• Hybrid work flexibility with occasional client or team site visits

If you're passionate about building impactful AI systems that solve real problems — and want to work at the intersection of innovation, sustainability, and sovereignty — this is your opportunity.