AI Engineer

Description Who Are We We Are Foodics! a leading restaurant management ecosystem and payment tech provider. Founded in 2014 with headquarters in Riyadh and offices across 5 countries, including UAE, Egypt, Jordan and Kuwait. We are currently serving customers and partners in over 35 different countries worldwide.

Our innovative products have successfully processed over 6 billion (yes, billion with a B) orders so far! making Foodics one of the most rapidly evolving SaaS companies to ever emerge from the MENA region.

Also, Foodics has achieved three rounds of funding, with the latest raising $170 million in the largest SaaS funding round in MENA, boosting its innovation capabilities to better serve business owners.

The Job in a Nutshell You will construct agentic AI architecture, leveraging large language models to orchestrate planning, execution, and tool interactions with minimal supervision.

Working within a compact engineering team, you will build the core foundational infrastructure, spanning microservices, integration protocols, state management, tracing, and eval harnesses, ensuring systems are production-ready, reliable, and scalable.

This hands-on backend software engineering position focuses primarily on coding, testing, and system diagnostics. While prompt design is incorporated into the workflow, complex architectural challenges reside within the underlying infrastructure. We welcome applicants across diverse seniority levels.

Given that production-grade agentic engineering remains an emerging discipline, candidates bring varied expertise candidate capability determines final level placement. Opportunities exist for early-career developers through veteran software architects. Engineering excellence remains mandatory across all levels.

Junior engineers pair directly with senior mentors to own production components within three months, while senior engineers drive technical standards and architectural vision.

What You Will Do

Architect and maintain agent infrastructure, including orchestration logic, session handling, state management, and reliable backend service interfaces. Design robust tool integrations and MCP servers featuring precise boundary definitions and comprehensive error recovery handlers.

Implement end-to-end tracing and observability for model calls, retrieval, and tool executions adhering to OpenTelemetry GenAI standards. Construct evaluation suites, benchmarks, and regression tests to validate model iterations and systematically capture production edge cases.

Perform deep-dive root cause analysis on runtime failures, loops, context degradation, or hallucinated outputs to strengthen system resiliency. Enforce runtime guardrails, cost thresholds, RBAC permissions, output validation schemas, and human-in-the-loop validation triggers.

Monitor industry advancements, emerging AI research, and architectural patterns, sharing technical insights across the engineering organization. What Are We Looking For Essential Deep software engineering expertise in a modern programming language, prioritizing algorithmic depth over superficial multi-language breadth.

Strong computer science foundations in data structures, algorithms, memory allocation, and concurrent execution patterns. Practical experience with backend infrastructure: REST/gRPC APIs, relational/non-relational databases, caching tiers, message queues, and distributed systems resilience.

Proficiency with Git, automated testing frameworks, CI/CD pipelines, and writing clean, maintainable software. Comprehensive mental model of LLM mechanics: context window constraints, tokenization, function calling protocols, non-deterministic behaviors, and hallucination management.

Demonstrated history of delivering full-lifecycle technical projects across production environments, academic work, open source, or side initiatives. Methodical debugging skills with the ability to articulate systematic troubleshooting methodologies. Strong technical documentation and written c