
Software Engineer AI - Alexandria
Sana Commerce · Alexandria, Alexandria Governorate, Egypt · Hybrid
- Software & SaaS
- 201–500 employees
- Rotterdam, South Holland
All reasons
In its favour
- Still listed on the employer's own board
What you'll be doing
- Design, develop, and deliver AI-powered features in Sana Commerce – agents that act on real commerce data (catalog, pricing, inventory, orders)
- Work with modern LLM frameworks and toolchains (e.g. any of Lang*, AWS Bedrock, MS Foundry, Cloudfare Agents, etc…)[VL1.1] to build RAG systems, AI Agents, and dynamic workflows – while understanding the raw agentic loop underneath them
- Work in a cross-functional team (Engineering, Product, Design) to integrate AI seamlessly into a distributed product
- Apply solid AI engineering principles end to end, from context and tool design through evaluation, deployment and continuous improvement
- Build the eval and feedback loops that gate releases: curated datasets, metrics and thresholds that block a regression the way a failing test does
- Design for failure by building the recovery path before the happy path
- Contribute to LLMOps and AI observability, improving reliability, evaluation, and monitoring pipelines
- Stay on top of emerging AI tools and frameworks, helping shape the vision and roadmap of Sana Commerce
What you bring
- Proven commercial experience building and deploying production-grade AI applications.
- 4+ years of web application engineering experience
- Strong software engineering (back-end, front-end nice to have) and SDLC fundamentals (design patterns, SOLID principles, experience with building complex MACH systems, CI/CD, testing)
- Apply strong backend and system design principles to ensure deterministic behaviour where needed, clear failure handling, human-in-the-loop controls, and production readiness.
- Practical knowledge of LLMs, their components (tokenization, attention, embeddings, vector search), and common limitations
- Hands-on experience with RAG pipelines, agents, and Vector Stores and the judgement to know when retrieval is the wrong tool
- Familiarity with LLMOps practices, monitoring, evaluation, and feedback loops.
- Has built real evals that are tied to business impact– dataset, metrics, thresholds and can name the regression they caught
- Cost and latency literacy – can say what a run costs and how to halve it
- Strong working knowledge of Cloud technologies
Ready to build reliability that scales?
Apply now and help shape the foundation of our next-generation SaaS platform.
#LI-JS1
#LI-Hybrid
Skills
- LLM
- Bedrock
- Foundry
- Retrieval-Augmented Generation
- LLMOps
- Embeddings
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