Software Engineer

Job Overview We are hiring engineers who build with agents, not just with editors. Mumzworld is the largest mother, baby and child e-commerce platform in the Middle East — millions of customers, a deep catalogue, and a stack that has to stay fast, correct and cheap at scale. We are rebuilding how our engineering team works around AI: agents write, review and test alongside us, and the engineers who compound fastest are the ones who know how to direct them. This is a backend-heavy full stack role. You will own services end to end — schema to API to the React surface that consumes it — and you will be expected to ship at a pace that only makes sense if you are genuinely fluent with modern AI tooling. Key Responsibilities • Own backend services end to end. Design, build and operate NestJS/TypeScript services on PostgreSQL — data modelling, APIs, background jobs, caching, observability, on-call for what you ship. • Close the loop on the frontend. Build the React interfaces that consume your APIs. You should be comfortable shipping a feature all the way to the customer without a handoff. • Work at real e-commerce scale. Catalogue, cart, checkout, pricing, promotions, inventory, order orchestration — systems where correctness and latency both matter, in two languages and multiple markets. • Build with agents by default. Use Claude Code and similar tooling as a core part of your workflow: planning, implementation, refactors, test generation, migrations, incident triage. • Make the team faster, not just yourself. Author agent skills, subagents and workflows that other engineers reuse. Wire up MCP servers to our internal systems. Turn tribal knowledge into tooling. • Ship AI into the product. Build LLM-powered features — search and discovery, content generation, support automation, merchandising assistance — with proper evals, guardrails and cost/latency budgets. • Raise the bar on quality. Strong code review, meaningful tests, and a healthy scepticism about agent-generated code that looks right. WHAT "AI-NATIVE" MEANS HERE Not "I use Copilot sometimes." Concretely, we expect you to: • Drive a coding agent through a non-trivial change — scoping context, breaking work down, iterating on failures — rather than accepting the first output. • Write agent skills and reusable prompts/workflows that encode how work should be done in a specific codebase or domain. • Compose multi-step and multi-agent workflows for things like large refactors, test backfills, dependency upgrades and codebase audits. • Understand MCP (Model Context Protocol) — and be able to build or integrate a server that gives agents safe access to a real system. • Evaluate LLM output properly: eval sets, regression checks, cost and latency tracking. If you cannot measure it, you cannot ship it. • Know where agents fail — and review their output like you would a talented but overconfident junior engineer. Requirments • 3+ years building and running production software, with backend as your centre of gravity. • Strong TypeScript/Node.js; production experience with NestJS or a comparable structured framework. • Solid PostgreSQL — schema design, indexing, query tuning, migrations, transactions. You know why your query is slow. • Working React proficiency — you can build and ship a clean, performant UI. • Real experience with REST/GraphQL API design, async patterns (queues/events), caching and integration with third-party systems. • Comfort with cloud infrastructure, CI/CD, Docker and modern observability tooling. • Demonstrable, daily use of AI coding agents — and an opinion about how to use them well. • Clear written communication. In an AI-native team, the quality of your writing is the quality of your engineering. BONUS POINTS • E-commerce, marketplace, retail or logistics systems experience. • Built and shipped an LLM feature into production — including the unglamorous parts (evals, fallbacks, cost control). • Published MCP servers, agent skills, plugins or open-source tooling. • Experience with high-traffic systems, search relevance, or recommendation/personalisation. • Arabic/English bilingual product experience. OUR STACK TypeScript • Node.js • NestJS • React • PostgreSQL • Redis • REST & GraphQL • Docker • AWS • GitHub Actions • Claude Code and agentic tooling throughout. WHY MUMZWORLD • The region’s category leader — real scale, real customers, real problems. • An engineering org actively investing in AI-native ways of working, not just talking about them. • Small teams, high ownership, short path from idea to production. • Competitive package, health cover, and a genuine say in the tools you use. Show more Show less

3+ years building and running production software, with backend as your centre of gravity. Strong TypeScript/Node.js; production experience with NestJS or a comparable structured framework. Solid PostgreSQL — schema design, indexing, query tuning, migrations, transactions. You know why your query is slow. Working React proficiency — you can build and ship a clean, performant UI. Real experience with REST/GraphQL API design, async patterns (queues/events), caching and integration with third-party systems. Comfort with cloud infrastructure, CI/CD, Docker and modern observability tooling. Demonstrable, daily use of AI coding agents — and an opinion about how to use them well. Clear written communication. In an AI-native team, the quality of your writing is the quality of your engineering.

Own backend services end to end. Design, build and operate NestJS/TypeScript services on PostgreSQL — data modelling, APIs, background jobs, caching, observability, on-call for what you ship. Close the loop on the frontend. Build the React interfaces that consume your APIs. You should be comfortable shipping a feature all the way to the customer without a handoff. Work at real e-commerce scale. Catalogue, cart, checkout, pricing, promotions, inventory, order orchestration — systems where correctness and latency both matter, in two languages and multiple markets. Build with agents by default. Use Claude Code and similar tooling as a core part of your workflow: planning, implementation, refactors, test generation, migrations, incident triage. Make the team faster, not just yourself. Author agent skills, subagents and workflows that other engineers reuse. Wire up MCP servers to our internal systems. Turn tribal knowledge into tooling. Ship AI into the product. Build LLM-powered features — search and discovery, content generation, support automation, merchandising assistance — with proper evals, guardrails and cost/latency budgets. Raise the bar on quality. Strong code review, meaningful tests, and a healthy scepticism about agent-generated code that looks right.