AI & LLM Solution Architect

Jobtailor; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Jobtailor in London seeks an AI Solutions Architect to design end-to-end AI/LLM solutions for enterprise customers, leveraging Tencent Cloud TokenHub, foundation models, AI Agents, and MCP ecosystem.

You will lead technical discovery workshops, architecture design sessions, POCs, validation, and production deployment planning, collaborating with customer engineering teams to deliver scalable, reliable AI systems.

Qualifications

• Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline.
• Minimum 2 years of experience in Generative AI, LLMs, ML, AI platforms, cloud computing, MLOps, or customer-facing technical consulting.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, MCP, model fine-tuning, and cloud-native AI architectures.
• Experience deploying enterprise AI applications on public clouds and in production environments.
• Strong English communication and ability to translate business requirements into scalable AI solutions.

Responsibilities

• Partner with enterprise customers to understand business challenges and identify AI transformation opportunities.
• Design end-to-end AI and LLM solutions leveraging Tencent Cloud TokenHub, foundation models, AI Agents, MCP ecosystem, and enterprise AI capabilities.
• Lead technical discovery workshops, architecture design sessions, POCs, technical validation, and production deployment planning.
• Work with customer engineering teams during implementation and production rollout.
• Troubleshoot complex technical issues and optimise AI application performance in enterprise production environments.
• Design scalable enterprise AI architectures using LLMs, Prompt Engineering, RAG, AI Agents, MCP, fine-tuning, inference optimisation, vector databases, API integration, workflow orchestration, and cloud-native AI services.
• Collaborate with Product, Engineering, and Research teams to translate customer requirements into platform enhancements.
• Develop reference architectures, implementation frameworks, sample applications, technical playbooks, and best practices.
• Support strategic enterprise opportunities through technical proposals, architecture reviews, executive presentations, tender responses, and technical due diligence.

Skills

Generative AI

Large Language Models

Prompt Engineering

AI Orchestration Frameworks

Cloud-Native AI Architectures

Solution Architecture

MLOps

Enterprise AI

Technical Consulting

Education

Bachelor's degree in Computer Science or related

Tools

Tencent Cloud TokenHub

MCP Ecosystem

AI Agents

Vector Databases

Workflow Orchestration

Job description

• Partner with enterprise customers to understand business challenges and identify AI transformation opportunities
• Design end-to-end AI and LLM solutions leveraging Tencent Cloud TokenHub, foundation models, AI Agents, MCP ecosystem, and enterprise AI capabilities
• Lead technical discovery workshops, architecture design sessions, POCs, technical validation, and production deployment planning
• Work with customer engineering teams during implementation and production rollout
• Troubleshoot complex technical issues and optimise AI application performance in enterprise production environments
• Design scalable enterprise AI architectures using LLMs, Prompt Engineering, RAG, AI Agents, MCP, fine-tuning, inference optimisation, vector databases, API integration, workflow orchestration, and cloud-native AI services
• Collaborate with Product, Engineering, and Research teams to translate customer requirements into platform enhancements
• Develop reference architectures, implementation frameworks, sample applications, technical playbooks, and best practices
• Support strategic enterprise opportunities through technical proposals, architecture reviews, executive presentations, tender responses, and technical due diligence

Requirements

• Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, or a related technical discipline
• Minimum 2 years of experience in Generative AI, Large Language Models (LLMs), machine learning, AI platforms, cloud computing, software engineering, MLOps, solution architecture, or customer-facing technical consulting
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, MCP, model fine-tuning, inference optimisation, vector databases, AI orchestration frameworks, API integration, and cloud-native AI architectures
• Experience developing or deploying enterprise AI applications on public cloud platforms
• Practical knowledge of multi-model AI orchestration, model deployment, inference services, observability, and production operations
• Strong customer-facing communication, presentation, analytical, and problem-solving skills
• Ability to translate complex business requirements into scalable AI solutions
• Excellent written and spoken English
• Proficiency in Chinese Mandarin
• Self-driven with strong learning agility, curiosity for emerging AI technologies, and ability to thrive in a fast-paced customer-facing environment

Core Competencies

Demonstrates expertise in designing and implementing scalable AI solutions using Large Language Models (LLMs) and cloud-native architectures, while effectively collaborating with enterprise customers to address their business challenges. Proficient in technical communication and problem-solving within fast-paced environments.

Highest-signal resume keywords

• Generative AI
• Large Language Models (LLMs)
• Prompt Engineering
• AI Orchestration Frameworks
• Cloud-Native AI Architectures

Hard Skills

• Machine Learning
• Model Fine-Tuning
• Inference Optimization
• Vector Databases
• API Integration
• Solution Architecture
• MLOps
• Technical Consulting
• Enterprise AI Applications
• Cloud Computing

Soft Skills

• Customer-Facing Communication
• Analytical Skills
• Problem-Solving Skills
• Presentation Skills
• Learning Agility

Industry Keywords

• Technical Discovery Workshops
• Architecture Design
• Production Deployment
• Technical Validation
• Enterprise AI Capabilities

Tools & Technologies

• Tencent Cloud TokenHub
• MCP Ecosystem
• AI Agents
• AI Transformation
• Workflow Orchestration