AI Developer

Location: Dubai / London / Remote | Engagement: Full-time or project-based | Experience: 3+ years preferred | Reports to: Technology Lead / Founder

Create useful AI-powered experiences for learners, faculty and internal operations, from content assistance and discovery to learner support and workflow automation. Prioritise measurable value, trustworthy outputs and responsible handling of data.

What you will own

• Build and maintain LLM-enabled product features, agents, retrieval systems and integrations.

• Develop AI-supported learning recommendations, knowledge search and personalised learner assistance.

• Help faculty create or adapt teaching materials with appropriate human review and quality controls.

• Automate repeatable internal workflows while maintaining clear approval and escalation points.

• Design evaluations for accuracy, usefulness, latency, safety and costs.

• Implement safeguards for privacy, security, role-based access and prompt-injection resistance.

• Deploy production services with telemetry, monitoring, documentation and improvement cycles.

Required experience and capabilities

• 3+ years of software development, including hands-on AI/ML or LLM application development.

• Strong Python or TypeScript skills, APIs, databases, cloud deployment and version control.

• Hands-on experience with modern model APIs, RAG, embeddings, structured outputs and evaluation.

• Understanding of data handling, model limitations and production reliability.

• Ability to translate vague user problems into testable product requirements.

Nice to have

• Experience in edtech, knowledge graphs, learning analytics or multimodal content.

• Cost optimisation, fine-tuning, model routing and experimentation infrastructure.

• Experience shipping AI features to nontechnical users.

First 90 days

• Identify and rank AI use cases by impact, feasibility and risk.

• Launch one production pilot with an evaluation baseline and human-feedback loop.

• Create a reusable AI development and quality-assurance playbook.

Success measures

• User adoption, task completion, quality evaluation scores and time saved.

• Service reliability, response latency, incident rate and cost per successful task.

• Responsible handling of learner and faculty data.

Application: Please share a CV/profile, a short note on relevant experience and examples of work or projects where appropriate.