AI Engineer

About the Role

Saudi Azm is seeking a highly skilled and experienced AI Engineer to join our team in Riyadh, Saudi Arabia. This full-time role requires a professional with a strong background in software, DevOps, or platform engineering, including at least two years dedicated to applied AI or ML engineering. The successful candidate will be instrumental in designing, building, and operating advanced AI and MLOps systems, contributing to critical projects within a dynamic environment.

Key Responsibilities: AI Systems

• Build, fine-tune, and evaluate LLM systems for domain-specific tasks, utilizing techniques such as QLoRA / PEFT on open-weight models like Llama-3 and Mistral.
• Design reproducible evaluation harnesses and A/B test frameworks with tracked metrics including task success rate, safety rate, and latency distributions (p50/p95).
• Architect multi-agent and RAG systems using tools like LangGraph, FastAPI, and vector databases, guiding them from prototype through production deployment.
• Implement safety guardrails, including input/output validation, allowlist/denylist policies, and controls to mitigate invalid or high-risk model actions.
• Translate business use cases into deployable prototypes with measurable acceptance criteria, and demonstrate them to stakeholders.

Key Responsibilities: Platform & Infrastructure

• Design and operate cloud infrastructure and MLOps workspaces (Azure, OCI, or GCP) for AI workloads on Kubernetes and containerized runtimes.
• Build CI/CD pipelines and implement GitOps-based release promotion (Argo CD) across development, test, and production environments.
• Implement end-to-end observability solutions (Azure Monitor, Application Insights, ELK) with defined detection and response targets.
• Apply network and perimeter security baselines (FW/WAF), automated code quality and SCA scanning (SonarQube, Black Duck), and gated pipelines.
• Own disaster recovery design, including automated backups, failover mechanisms, and documented RTO/RPO commitments.

Key Responsibilities: Engineering Leadership

• Lead and mentor a cloud/AI operations team, defining monitoring, incident response, and release governance practices with clear uptime and MTTR targets.
• Standardize SDLC practices, including branching strategy, PR governance, release management, and delivery reporting, to improve lead time and deployment frequency.
• Consolidate engineering tooling and workflows, driving migrations and platform standardization where fragmentation impedes delivery.
• Produce handover documentation and runbooks to ensure systems are auditable and operationally transferable.
• Support vendor and licensing negotiations for cloud enterprise agreements.

Required Qualifications and Experience

• Bachelor's degree in Software Engineering, Computer Science, or a related field.
• 6–8+ years of experience in software, DevOps, or platform engineering, with at least 2 years in an applied AI or ML engineering capacity.
• Proven track record of delivering production AI/LLM systems, beyond research or notebook-stage work.
• Strong proficiency in Python; comfortable with Bash and YAML.
• Deep hands-on experience with Kubernetes, Docker/Podman, and Terraform.
• Production experience with at least one major cloud platform (Azure preferred; OCI or GCP acceptable).
• Demonstrated ownership of CI/CD at scale (Azure DevOps, GitHub Actions) and GitOps release models.
• Experience leading a team and setting engineering standards across multiple squads.

Preferred Qualifications

• Master's degree in Applied AI, Machine Learning, or a related discipline.
• Fine-tuning experience with QLoRA/LoRA on GPU clusters, utilizing PyTorch and Transformers.
• Experience with vector databases (Milvus, Pinecone, or Weaviate) and RAG retrieval design.
• Experience delivering on Saudi government or large-scale national digital platforms, with familiarity in local compliance and standards.
• Professional proficiency in both Arabic and English.