At a Glance
- Tasks: Design and deliver cutting-edge AI solutions for enterprise customers.
- Company: Join Carbon3, a leader in sustainable AI infrastructure.
- Benefits: Competitive salary, equity participation, and performance rewards.
- Other info: Collaborate with industry leaders and enjoy excellent growth opportunities.
- Why this job: Shape the future of AI while making a real-world impact.
- Qualifications: 5+ years in AI/ML engineering with strong coding skills.
The predicted salary is between 60000 - 84000 € per year.
Senior AI Solutions Engineer
About
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.
The Role:
We\'re seeking a Senior AI Solutions Engineer 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 \'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 \'s AI solutions.
Revenue Contribution
- Support pre-sales activities resulting in measurable influenced ARR aligned with GTM metrics.
Required Qualifications
- 5+ years in 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
. - Experience working directly with enterprise customers and translating technical concepts into business value.
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
- 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, equity participation, and performance-linked rewards.
Senior AI Solutions Engineer in London employer: Carbon3 - The UK's AI Solution Platform
At Carbon3, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior AI Solutions Engineer, you'll have the opportunity to work at the cutting edge of AI technology while engaging with enterprise customers to drive meaningful transformation. With competitive compensation, equity participation, and a commitment to employee growth through mentorship and knowledge sharing, Carbon3 is dedicated to empowering its team members in a fast-paced, high-investment environment focused on sustainable innovation.
Contact Detail:
Carbon3 - The UK's AI Solution Platform Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Solutions Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and tech space. Attend meetups, webinars, or industry events where you can chat with potential employers and showcase your skills.
✨Tip Number 2
Show off your expertise! Create a portfolio of your projects, especially those involving RAG pipelines or fine-tuning models. This will give you a leg up when discussing your experience with hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on common AI and ML questions. Be ready to discuss how you've tackled real-world problems using AI solutions, and don’t forget to highlight your customer engagement skills!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us at Carbon3. Tailor your application to show how your skills align with our mission of building sustainable AI solutions.
We think you need these skills to ace Senior AI Solutions Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior AI Solutions Engineer role. Highlight your experience with RAG pipelines and fine-tuning LLMs, as these are key aspects of the job. We want to see how your skills align with our mission!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention your experience with tools like PyTorch, HuggingFace, and any relevant coding languages. We’re looking for someone who can hit the ground running, so let us know what you bring to the table.
Engage with Our Values:In your application, reflect on how your personal values align with our commitment to sustainable innovation and customer-centric solutions. We love seeing candidates who resonate with our mission and can contribute to our culture.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Carbon3!
How to prepare for a job interview at Carbon3 - The UK's AI Solution Platform
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like RAG pipelines and PyTorch. Brush up on your coding skills in Python and be ready to discuss how you've implemented these technologies in past projects.
✨Understand the Business Side
Since this role blends technical expertise with commercial acumen, prepare to talk about how your AI solutions have driven business value. Think of specific examples where your work has solved customer challenges or improved processes.
✨Prepare for Customer Engagement Scenarios
As a customer-facing role, practice how you would engage with enterprise customers. Be ready to discuss how you would map their business goals to AI workflows and design solutions that meet their needs.
✨Showcase Your Collaboration Skills
Collaboration is key in this role, so think of examples where you’ve worked closely with other teams, like sales or infrastructure. Highlight any mentoring experiences you have, as they’ll want to see your ability to train junior engineers.
