AI Intern
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Key skills for this role
About the Role
Tabby builds financial products used by millions of users across the GCC. Alongside core fintech products, we are actively building internal platforms for AI a.
Key Skills for This Role
Responsibilities
- Build AI agents and automations using internal no code and low code tooling
- Configure agent workflows, tools, and orchestration logic
- Integrate agents with internal systems via APIs and tools
- Participate in designing agent architectures and workflows
- Help test, evaluate, and iterate on agent behavior and quality
- Work with datasets and evaluation results to improve agent performance
- Document agent logic, workflows, and best practices
- Work closely with platform engineers, product managers, and internal users
Requirements
- Strong logical and systems thinking
- Ability to break down human workflows into structured steps
- Understanding of how web services, APIs, and tools interact
- Experience with no code or low code platforms
- Basic understanding of data formats (JSON), APIs, and webhooks
- Ability to reason about edge cases, failure modes, and correctness
- High level of ownership and responsibility
- Comfort with fast iteration and experimental environments
- English sufficient for documentation and team communication
- Saudi nationals only
Full Job Posting
About the company
- Tabby builds financial products used by millions of users across the GCC.
- Alongside core fintech products, we are actively building internal platforms for AI agents and LLM based automation used across the company.
- This internship is not educational by default. It is an engineering adjacent role with real production impact.
Context
- The AI Agents Platform team builds an internal platform that allows teams across Tabby to create, run, evaluate, and iterate on AI agents.
- These agents automate real human workflows: customer support, operations, fraud checks, data validation, and internal tooling.
- The platform is young, evolving fast, and already used by multiple teams.
- The internship is designed for candidates who are comfortable working in ambiguous, experimental environments and can think in systems rather than isolated tasks.
What you will do
- Build AI agents and automations using internal no code and low code tooling
- Configure agent workflows, tools, and orchestration logic
- Integrate agents with internal systems via APIs and tools
- Participate in designing agent architectures and workflows
- Help test, evaluate, and iterate on agent behavior and quality
- Work with datasets and evaluation results to improve agent performance
- Document agent logic, workflows, and best practices
- Work closely with platform engineers, product managers, and internal users
Required
- Strong logical and systems thinking
- Ability to break down human workflows into structured steps
- Understanding of how web services, APIs, and tools interact
- Experience with no code or low code platforms
- Basic understanding of data formats (JSON), APIs, and webhooks
- Ability to reason about edge cases, failure modes, and correctness
- High level of ownership and responsibility
- Comfort with fast iteration and experimental environments
- English sufficient for documentation and team communication
Strong plus
- Experience with LLMs, AI agents, or automation
- Experience building internal tools or automations
- Experience with Python
- Education in data science, machine learning field
- Understanding of prompt design or agent orchestration concepts
- Familiarity with evaluation, testing, or quality metrics
- Curiosity about AI system behavior and limitations
What we do not expect
- Expert level knowledge of LLMs, agent frameworks, or prompt engineering
- Prior professional AI, automation, or platform engineering experience
- Mastery of all listed no code platforms or LLM tooling
- Deep knowledge of ML internals, model training, or RAG architectures
Eligibility
- Saudi nationals only
- Self funded internship by Tabby
- We welcome both current students and fresh grads
- We expect a full time level of engagement throughout the internship.
- The program is not part time: interns should be ready to contribute at a full working day pace.
- We understand that students may occasionally need flexibility for classes or exams, which can be aligned with the mentor in advance, but overall performance, ownership, and context involvement are expected at a full time level.
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