Senior AI Systems Engineer — LLMs, RAG & MLOps Lead

azmtalent; Saudi Arabia; On-site; SAR 240,000 - 360,000; Full time

Job summary

azmtalent is seeking an experienced AI systems leader in Saudi Arabia to build, fine-tune, and evaluate domain-specific LLMs using QLoRA/PEFT on open-weight models. You will architect multi-agent and RAG systems, design evaluation harnesses, and drive production readiness from prototype to deployment.

The role requires 6–8+ years in software/DevOps with hands-on Kubernetes, Terraform, and cloud experience across Azure, OCI, or GCP. Strong leadership and SDLC governance are essential for success.

Qualifications

• Bachelor's degree in software engineering or computer science.
• 6–8+ years in software, DevOps, or platform engineering with AI exposure.
• Proven delivery of production AI/LLM systems, not just research.
• Strong Python; proficient with Bash and YAML.
• Hands-on Kubernetes, Docker/Podman, and Terraform experience.

Responsibilities

• Build, fine-tune, and evaluate LLM systems for domain tasks.
• Architect multi-agent and RAG systems from prototype to production.
• Design reproducible evaluation harnesses and tracked metrics.
• Lead and mentor a cloud/AI operations team with governance.
• Own SDLC standards and platform standardization across squads.

Skills

Leadership

Team mentoring

Engineering standards

Cross-squad coordination

Documentation

Education

Bachelor's degree in Software Engineering or Computer Science

Master's degree in Applied AI (preferred)

Tools

Python

Bash

YAML

Kubernetes

Docker/Podman

Terraform

Azure DevOps

GitHub Actions

Argo CD

Azure Monitor

Application Insights

ELK

LangGraph

Milvus

Pinecone

Weaviate

Job description

azmtalent is seeking an experienced AI systems leader in Saudi Arabia to build, fine-tune, and evaluate domain-specific LLMs using QLoRA/PEFT on open-weight models. You will architect multi-agent and RAG systems, design evaluation harnesses, and drive production readiness from prototype to deployment.

The role requires 6–8+ years in software/DevOps with hands-on Kubernetes, Terraform, and cloud experience across Azure, OCI, or GCP. Strong leadership and SDLC governance are essential for success.