AI Agent Analyst Engineer (Paarl)

Are you passionate about Data, Artificial Intelligence, and intelligent automation? We’re looking for a talented Data and AI Agent Analyst Engineer to join a forward-thinking technology team and help design, develop, and optimise AI-powered solutions that transform the way businesses work.
In this role, you’ll work at the intersection of data analytics, AI agents, automation, and engineering, turning complex business challenges into intelligent, scalable solutions. If you’re curious, analytical, technically minded, and excited about the future of AI, this could be an excellent opportunity to make a meaningful impact.

What we’re looking ofr:

• Bachelor’s degree or higher in data science, computer science, business analysis, finance, or a related field (required)
• Minimum 5 years’ working experience in a data analyst, BI, or similar data-focused role (required)
• Hands-on experience building or working closely with AI agents, LLM applications, or automation solutions (required)
• Strong proficiency in SQL (PostgreSQL) and Python for data cleaning, analysis, and building AI/automation solutions
• Familiarity with LLMs, prompt engineering, and agent frameworks, plus concepts like RAG and model evaluation
• Experience with data visualisation / BI tools and advanced Excel (Power Query, Power Pivot, data models)
• Working knowledge of APIs, automation tools (Make), Docker, and GitHub
• Experience in the Fintech / SaaS industry (advantageous)
• Working experience in the South African financial services / financial planning industry (advantageous)
• Excellent written and verbal communication skills (English, Afrikaans advantageous)

What you will be doing:

• You will own the delivery of reports, dashboards, and analytics that our business and clients rely on, while also designing, building, and improving AI agents that automate the work behind the scenes and power new features in the Commspace product. You will use your out-of-the-box thinking to spot where AI and automation can make a real difference, and then make it happen.
• Here is what your day-to-day would look like:
• Data analysis and reporting
• Develop and maintain regular reports and dashboards for key business metrics.
• Create and optimise SQL queries for data extraction and analysis, applying advanced techniques such as window functions, stored procedures, materialised views, and query performance tuning.
• Design and implement data visualisation dashboards, generating actionable insights from complex datasets.
• Present findings to stakeholders in clear, concise formats and turn ad-hoc data requests around promptly (typically within 24 hours, depending on complexity and priority)