Artificial Intelligence Engineer

Roles & Responsibilities

• Design and develop AI models and algorithms from the ground up.
• Design, test, and refine prompts for Large Language Models (LLMs) to optimise performance across diverse use cases, aligning with business goals and user needs.
• Implement AI solutions that integrate seamlessly with existing business systems to improve functionality and user experience.
• Manage data pipelines and flows to ensure effective AI deployment.
• Collaborate cross-functionally to align AI initiatives with strategic organisational objectives.
• Participate in functional and process design including scenario design, flow mapping, prototyping, testing, training, and support documentation.
• Document solutions and lessons learned from each AI initiative or prototype.
• Lead and manage teams in conducting market and competitor analysis in the AI and automation space.
• Work closely with stakeholders and product teams to gather feedback and refine solutions based on performance and user interaction.
• Handle large-scale data sets for statistical modeling, data mining, and recommendation systems.
• Write production-grade code and ensure best practices in software development.
• Develop, fine-tune, and customise LLMs for specific business applications.
• Research and develop state-of-the-art AI technologies.
• Build and deploy scalable AI software systems.
• Collaborate with development teams to ensure seamless integration of AI applications into deployment pipelines.
• Provide post-deployment support and optimisation for AI solutions.
• Adhere to established development and support procedures.

Skills & Experience

Technical Skills:

• Strong foundation in computer science fundamentals including algorithms, data structures, and complexity analysis.
• Proven experience deploying applications on Kubernetes in cloud environments (AWS, Azure, GCP) using Helm charts and Docker Compose.
• Proficient in machine learning, deep learning, natural language processing (NLP), and computer vision.
• Experience designing and implementing MLOps pipelines with monitoring and observability.
• Familiarity with AI frameworks such as TensorFlow and PyTorch.
• 3-5 years of hands-on experience applying AI to practical, scalable technology solutions.
• Skilled in programming with Python and building/managing ML pipelines.
• Experience with REST API development, NoSQL and RDBMS database design and optimisation.
• Understanding of object-oriented and functional design principles, with knowledge of best-practice architectural patterns.
• Exposure to AWS/Azure DevOps tools and processes.

Non-Technical Skills:

• Excellent problem-solving skills and ability to thrive in a collaborative, team-oriented environment.
• Strong business acumen with a keen eye for detail.
• Effective communicator, capable of explaining complex technical concepts to non-technical stakeholders.
• Self-motivated and enthusiastic, with a proactive approach to team contribution and goal setting.
• Analytical mindset, capable of identifying user challenges and proposing creative, effective AI-driven solutions.