Artificial Intelligence Engineer

About the Role
We are looking for a hands-on AI Engineer with 2+ years of practical experience developing, integrating and deploying AI solutions in real-world environments.
This is a technical, hands-on role for someone who has actually built AI solutions, rather than someone whose experience is primarily theoretical or limited to using AI tools.
The successful candidate will work on AI-powered applications, intelligent automation, LLM integrations and AI agent solutions within a technology-focused environment.
Key Responsibilities
Design, develop and implement AI-powered applications and solutions.
Build and integrate LLM and Generative AI solutions into software applications.
Develop AI agents, intelligent workflows and AI-powered automation.
Integrate AI models and APIs into existing applications and platforms.
Develop high-quality, maintainable Python code.
Build and consume REST APIs and third-party integrations.
Work with databases, data pipelines and AI-related data structures.
Implement RAG, embeddings and vector search solutions where required.
Develop prompt engineering strategies and structured AI workflows.
Test, debug and optimise AI applications and models.
Evaluate AI outputs and improve accuracy, reliability and performance.
Deploy and maintain AI solutions in production environments.
Troubleshoot technical issues and continuously improve existing solutions.
Collaborate with developers, product teams and business stakeholders.
Research and implement relevant emerging AI technologies and tools.
Minimum Requirements
2+ years of hands-on experience in AI Engineering, Machine Learning Engineering, Software Engineering with an AI focus, or a closely related role.
Strong Python development experience.
Demonstrable experience building and deploying real-world AI applications.
Hands-on experience working with LLMs / Generative AI.
Experience integrating AI APIs such as OpenAI, Anthropic, Gemini or similar.
Experience developing AI-powered applications rather than simply using AI tools.
Experience with REST APIs and software integrations.
Experience with Git and modern software development practices.
Experience working with databases.
Understanding of prompt engineering and AI application architecture.
Strong debugging and problem-solving abilities.
Ability to work independently in a fully remote environment.
Strong written and verbal English communication.
Advantageous Experience
LangChain, LangGraph, LlamaIndex or similar AI frameworks.
RAG systems and vector databases.
AI agents and agentic workflows.
Function/tool calling.
Open-source LLMs and model deployment.
FastAPI or similar Python frameworks.
Docker.
AWS, Azure or GCP.
PyTorch, TensorFlow or other machine learning frameworks.
CI/CD and production deployment.
Experience developing SaaS or technology products.
Experience with AI automation platforms and workflow tools.
Hands-On Experience – Essential
Candidates should be able to demonstrate actual projects they have built or contributed to, including their specific technical contribution.
Examples may include:
AI agents
LLM-powered applications
RAG systems
AI chatbots
AI automation systems
Document intelligence solutions
AI-powered SaaS features
Model/API integrations
Intelligent workflow automation
Production AI applications
Candidates should ideally be able to provide GitHub, portfolio or project examples demonstrating their practical experience.
What We Are Looking For
We are looking for an engineer who is technically hands-on, curious, practical and comfortable building solutions from the ground up.
The ideal candidate can take an AI concept, develop the solution, integrate the required technologies, test it and help get it into a working production environment.
Candidates with only academic AI/ML knowledge, prompt-only experience, or experience using ChatGPT/AI tools without actually developing AI solutions will not be suitable.

Work arrangement
Yes