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Foodics is a leading restaurant management ecosystem and payment tech provider founded in 2014, headquartered in Riyadh with offices across 5 countries. The company has processed over 6 billion orders and recently raised $170 million in the largest SaaS funding round in MENA.
You will oversee the quality assurance process for product updates prior to launch, working closely with development teams throughout the product development lifecycle. This role bridges traditional test automation with cutting-edge AI-driven quality practices.
**Core Responsibilities:**
Test automation across the full stack: Backend API and contract testing with service-level and integration coverage; Frontend web E2E and component-level coverage using Playwright with visual and RTL regression; Mobile native and cross-platform coverage with Appium or Maestro, including device-farm strategy and payment-peripheral paths; Shared fixtures, environment and test-data management, parallelization, and CI pipelines; Performance and load testing.
AI-layer quality tooling: Test generation from specs, code, and production traffic with maintenance solutions; Failure triage that classifies red builds (real bug, flake, environment, or test rot) before human review; Self-healing locators and suite health tooling including flake detection and coverage-gap analysis; Evaluation infrastructure for AI features with datasets and regression detection; Region-specific evaluation for Arabic/English behavior, RTL interfaces, and MENA-specific POS, tax, and payment rules.
Agentic AI and orchestration: Build agentic AI that performs real work in pipelines—reading diffs, running relevant suites, reproducing failures, proposing fixes, and opening PRs; Agents that own quality workflows end-to-end (exploratory testing, coverage-gap hunting, release-risk assessment) with human escalation; Orchestration handling multi-step planning, tool use, retries, state management, sandboxed execution, and multi-agent handoffs; Integration with existing stack (CI, Jira, observability, MCP-style interfaces) rather than parallel systems; Judgment to know when plain pipelines beat agents.
You will stay current on modern test automation frameworks (Playwright, Appium, Maestro), agentic AI orchestration and tool use, context engineering (retrieval, chunking, reranking, caching), evaluation methodologies (offline/online evals, LLM-as-judge, human-in-the-loop), reliability patterns (structured output, guardrails, fallback design), and LLM operations (tracing, observability, prompt management, latency/cost budgeting, model routing).
**Requirements:**
- Production software shipping experience with recent hands-on work on LLM-backed systems that real users depend on
- Strong Python; comfortable in at least one of .NET, Java, or TypeScript
- Tested, maintained code (not notebooks)
- Real automation depth across multiple surfaces (owned suites that gate releases on backend and UI—web or mobile—and kept them green without deleting hard tests)
- Real experience building evaluation systems with measurable improvements and numbers
- Practical depth with modern LLM toolkit: prompting, structured output, tool use, retrieval, agentic AI orchestration, with clear understanding of trade-offs
- Credible testing fundamentals: test design, automation frameworks, and CI/CD should not be new to you
- Bias toward adoption: measure work by what other engineers use, not by what you demoed
