Senior Pre Sales Engineer

Carbon3 is building the UK’s sovereign AI infrastructure platform, combining renewable energy, distributed compute, and full data ownership to power the next generation of sustainable innovation. We’re seeking a Senior Pre Sales Engineer who has expertise in AI solutions architecture to sit at the intersection of customer business challenges and cutting-edge AI technology. This is a hands-on, customer-facing role responsible for designing and delivering enterprise-grade AI solutions leveraging retrieval-augmented generation (RAG), fine-tuning, and inference deployment across Carbon3.ai’s sovereign AI Mesh. You’ll blend deep technical expertise with commercial acumen — engaging customers, architecting solutions, and ensuring seamless deployment of AI systems that drive real-world transformation. Key Responsibilities Customer Solution Design: Engage with enterprise customers to understand business goals and map them to AI workflows. Architect RAG pipelines, fine-tuning strategies, and inference endpoint deployments using our key products. Collaborate with GTM and sales teams during pre-sales cycles, workshops, and proof-of-concepts. AI And ML Engineering Implement, optimise, and deploy models using PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Execute fine-tuning and evaluation of foundation models for domain-specific use cases. Package and deploy models into scalable inference endpoints (REST/gRPC APIs, containerised or GPU-accelerated environments). Data And Knowledge Integration (RAG) Build pipelines that connect structured and unstructured enterprise data into vector databases and embedding models. Design semantic search and retrieval strategies to maximise response accuracy and relevance. Ensure all data pipelines are secure, compliant, and performant at scale. Collaboration And Knowledge Sharing Work closely with infrastructure and platform engineering teams for smooth deployments. Feed insights into the product roadmap and platform feature development. Act as a thought leader and trusted advisor to customers exploring applied AI adoption. Technical Excellence Develop and maintain 3–4 reusable solution accelerators (templates, playbooks, code repos) adopted across projects. Reduce model deployment cycle time by >30% through automation, tooling, or platform improvements. Collaboration And Growth Train or mentor at least 2 junior engineers or solution architects in AI delivery best practices. Contribute 2+ technical case studies, blog posts, or conference talks showcasing Carbon3.ai’s AI solutions. Revenue Contribution Support pre-sales activities resulting in measurable influenced ARR aligned with GTM metrics. Required Qualifications Experience working directly with enterprise customers and translating technical concepts into business value. Solid experience within AI/ML engineering, applied AI, or solutions engineering roles. Proven Experience With RAG pipelines (LangChain, LlamaIndex, Weaviate, Pinecone, Milvus, etc.) Fine-tuning LLMs (LoRA, PEFT, instruction-tuning, domain adaptation) Deploying inference endpoints at scale (Triton, HuggingFace Inference, Ray Serve, Kubernetes) Strong coding skills in Python (and ideally one of Go, Java, or C++). Deep understanding of vector databases, embeddings, and semantic search. Preferred Experience Exposure to NVIDIA AI Enterprise, HPE Private Cloud AI, or other enterprise AI platforms. Familiarity with UK regulatory and compliance frameworks (data sovereignty, ISO 27001, SOC 2). Knowledge of GPU optimisation and performance tuning. Contributions to open-source AI or ML projects. Why Join Carbon3.ai? Work with next-generation AI products Operate at the forefront: Join a fast-moving, high-investment market shaping the future of sovereign compute. Engage with senior leaders: Collaborate with executives across government, enterprise, and technology ecosystems. Influence market direction: Help position Carbon3 as the trusted platform for sustainable, sovereign AI adoption. Benefit from growth: Competitive compensation and performance-linked rewards. Location: This opportunity will require the successful individual to travel to customer sites across the United Kingdom.