AI Developer

We are seeking an innovative and technically skilled AI Developer to design, build, deploy and maintain artificial intelligence solutions that solve real business challenges. The successful candidate will work closely with cross-functional teams to develop machine learning models, generative AI applications, automation solutions and intelligent systems that drive efficiency, enhance customer experiences and support strategic business objectives.

Key Responsibilities

AI Solution Development

• Design, develop, test and deploy AI and machine learning solutions.
• Build and maintain scalable AI applications and APIs.
• Develop Generative AI solutions using Large Language Models (LLMs).
• Create AI-powered chatbots, virtual assistants and intelligent automation tools.
• Integrate AI capabilities into existing products, platforms and business processes.

Machine Learning & Model Management

• Collect, clean and prepare data for model training and evaluation.
• Develop, train, test and optimize machine learning models.
• Monitor model performance and retrain models when necessary.
• Implement MLOps practices to support model deployment and lifecycle management.
• Ensure model accuracy, reliability, scalability and security.

Software Development

• Write clean, efficient and maintainable code.
• Develop backend services, APIs and integrations supporting AI applications.
• Participate in code reviews and software development best practices.
• Troubleshoot and resolve technical issues related to AI systems.

Innovation & Research

• Stay current with advancements in AI, machine learning, automation and emerging technologies.
• Evaluate new tools, frameworks and AI platforms.
• Recommend and implement innovative solutions that create business value.
• Participate in proof-of-concepts and pilot projects.

Collaboration & Stakeholder Engagement

• Work closely with business stakeholders to understand requirements and opportunities for AI adoption.
• Translate business challenges into technical AI solutions.
• Collaborate with data engineers, software developers, product teams and business leaders.
• Present technical concepts and solution recommendations to both technical and non-technical audiences.

Governance, Security & Compliance

• Ensure AI solutions comply with data privacy, security and regulatory requirements.
• Support responsible and ethical AI practices.
• Document AI models, development processes and technical solutions.
• Contribute to AI governance and risk management initiatives.

Technical Skills

• Strong programming skills in Python.
• Knowledge of JavaScript, C#, Java or similar programming languages.
• Experience with AI/ML libraries such as TensorFlow, PyTorch, Scikit-learn, LangChain or Hugging Face.
• Experience working with Large Language Models (LLMs) and Generative AI.
• Knowledge of prompt engineering and retrieval-augmented generation (RAG) frameworks.
• Experience with SQL and database technologies.
• Familiarity with containerisation technologies such as Docker and Kubernetes.
• Understanding of MLOps and CI/CD practices.

Minimum Requirements

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology or related field.
• Relevant certifications in AI, Machine Learning, Cloud Technologies or Data Science would be advantageous.

Experience

• 3+ years software development experience.
• 2+ years experience developing AI or machine learning solutions.
• Experience working with cloud platforms such as Microsoft Azure, AWS or Google Cloud.
• Experience deploying AI applications into production environments.
• Experience with API development and integration.

Technical Competencies

• Artificial Intelligence Development
• Machine Learning Engineering
• Data Analysis and Modelling
• Software Development
• Cloud Computing
• Systems Integration
• API Development
• Problem Solving

Behavioural Competencies

• Innovation and Curiosity
• Critical Thinking
• Attention to Detail
• Collaboration and Teamwork
• Adaptability
• Continuous Learning
• Communication Skills
• Accountability and Ownership

Key Performance Indicators (KPIs)

• Successful deployment of AI solutions.
• Model performance and accuracy metrics.
• System reliability and uptime.
• Delivery of projects within agreed timelines.
• Automation and efficiency improvements achieved.
• User adoption and satisfaction rates.
• Reduction in manual effort through AI implementation.
• Compliance with security and governance standards.

What Success Looks Like

A successful AI Developer leverages technology to create intelligent solutions that improve business performance, automate repetitive processes, enhance customer experiences and unlock new opportunities through responsible and scalable AI innovation.