The Role
Key Responsibilities
- Build
recommendation engines, agentic AI frameworks, Retrieval-Augmented
Generation (RAG) solutions, and intelligent summarisation capabilities. - Engineer
solutions using large language models (LLMs) and foundation models to
support chatbots, semantic search, summarisation, and reporting use cases. - Own the
end-to-end AI/ML lifecycle, including problem definition, data
exploration, model development, validation, deployment, and monitoring. - Collaborate
with engineering, sales operations, and business stakeholders to embed
intelligent capabilities into reporting and analytics platforms. - Conduct
experimentation, statistical analysis, and causal inference studies to
evaluate business outcomes and solution effectiveness. - Stay
current with emerging AI and machine learning technologies and identify
opportunities for innovation.
Essential Skills & Experience
- Strong
understanding of software engineering best practices, including version
control, CI/CD, containerisation, monitoring, and deployment automation. - Experience
with modern AI frameworks such as FastAPI, LangChain, LlamaIndex, or
similar technologies. - Experience
working with large-scale datasets using SQL, distributed processing
platforms such as Spark, and cloud-based infrastructure. - Ability to
translate business challenges into scalable AI and machine learning
solutions.
Bachelor's degree in Computer Science, Engineering,
Statistics, Data Science, or equivalent practical experience.
