AI Engineer

Role Overview

AI Engineer at Foodics, a leading restaurant management ecosystem and payment technology provider headquartered in Riyadh with offices across 5 countries. The company serves customers and partners in over 35 countries worldwide.

Company Overview

Foodics was founded in 2014 and operates as a SaaS platform that has processed over 6 billion orders. The company has completed three funding rounds, with the latest raising $170 million in the largest SaaS funding round in MENA. Foodics employs over 30 nationalities working across 14 countries.

Role Purpose

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 core foundational infrastructure spanning microservices, integration protocols, state management, tracing, and evaluation harnesses, ensuring systems are production-ready, reliable, and scalable. This hands-on backend software engineering position focuses primarily on coding, testing, and system diagnostics.

Key Responsibilities

Architecture & Infrastructure

• Architect and maintain agent infrastructure, including orchestration logic, session handling, state management, and reliable backend service interfaces.
• Design robust tool integrations and Model Context Protocol servers featuring precise boundary definitions and comprehensive error recovery handlers.
• Enforce runtime guardrails, cost thresholds, RBAC permissions, output validation schemas, and human-in-the-loop validation triggers.

Observability & Testing

• 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.

Resilience & Optimization

• Perform deep-dive root cause analysis on runtime failures, loops, context degradation, or hallucinated outputs to strengthen system resiliency.
• Monitor industry advancements, emerging AI research, and architectural patterns, sharing technical insights across the engineering organization.

Qualifications & Experience

• 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.
• 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.

Skills & Competencies

• Proficiency with Git, automated testing frameworks, CI/CD pipelines, and writing clean, maintainable software.
• Methodical debugging skills with the ability to articulate systematic troubleshooting methodologies.
• Strong technical documentation and written communication skills to articulate complex distributed system behaviors.
• Hands-on experience developing application prototypes integrated with LLM APIs (nice to have).
• Familiarity with Model Context Protocol or custom tool integrations (nice to have).
• Understanding of vector database indexing, embedding generation, and retrieval pipelines (nice to have).
• Experience with cloud infrastructure, preferably AWS, containerization such as Docker/Kubernetes, telemetry, or Infrastructure as Code tooling (nice to have).
• Knowledge of GenAI security paradigms, prompt injection mitigation, and threat modeling (nice to have).
• Active open-source contributions or community engagement (nice to have).

Additional Information

Seniority Levels

Foodics welcomes applicants across diverse seniority levels. Candidate capability determines final level placement.

Early Career: Focuses on technical foundations, algorithmic problem-solving, and curiosity. Prior agentic experience is not required; mentorship is provided to expand scope over well-defined modules. Junior engineers pair directly with senior mentors to own production components within three months.

Mid-Level: Owns sub-systems end-to-end, translates ambiguous requirements into robust architecture, and demonstrates a proven track record of shipping and maintaining production services.

Senior Level: Drives strategic architectural direction, possesses hands-on experience scaling non-deterministic systems, elevates team-wide engineering practices, and actively challenges technical assumptions.

Technical Standards

• Model Context Protocol: Open standard managed via the Linux Foundation for integrating models with tool services and data stores.
• OpenTelemetry GenAI Conventions: Standardized instrumentation schemas for tracking model execution traces, step transitions, and tool invocations.
• OWASP GenAI & Agentic Security Guidelines: Threat modeling standards emphasizing containment strategies, least-privilege tooling, strict input sanitization, and authorization gates for critical actions.
• Eval-Driven Development: Mandatory evaluation validation prior to shipping behavioral changes, relying on internal domain-specific test harnesses rather than external benchmark metrics.

Benefits & Work Environment

• Inclusive and diverse culture that encourages innovation and flexibility in-office and hybrid work setups.
• Highly competitive compensation packages, including bonuses and the potential for shares.
• Personal development with regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
• Autonomy, mentoring, and challenging goals that create opportunities for both you and the company.