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AI Platform Engineer

Riyadh, Saudi Arabia

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About SYSMNT

  • SYSMNT is a technology implementation partner building enterprise systems and digital platforms across the Kingdom, working with clients in retail, hospitality, fuel and energy, and services.
  • AI is moving from pilot to production in our clients' operations, and the gap between a working prototype and a system a business can actually depend on is where this role sits. We're a lean team, so you'll be building the platform rather than maintaining one someone else designed.

The Role

  • You'll own the infrastructure that gets AI and ML workloads into production and keeps them there: serving, pipelines, monitoring, and the automation around all of it. That covers internal tooling as well as the AI capabilities we deliver inside client platforms — document processing, retrieval systems, forecasting, and automation layered on the business systems we implement.
  • The work is honest about where it sits: less frontier research, more making sure a model that worked in a notebook still works at 9am on a Sunday under real load with real data.

Responsibilities

Platform & Deployment

  • Design, deploy, and operate the infrastructure that runs AI and ML workloads in production
  • Containerize and orchestrate model serving using Docker and Kubernetes
  • Build and maintain deployment pipelines for models, from packaging through rollout and rollback
  • Manage GPU and compute resources, balancing cost against performance

MLOps & Tooling

  • Implement pipelines for training, evaluation, deployment, and monitoring
  • Set up model versioning, registries, and reproducible experiment tracking
  • Build data pipelines feeding model training and inference
  • Automate the repetitive parts so deployment isn't a manual ritual

Reliability & Observability

  • Instrument monitoring for latency, throughput, cost, and model quality in production
  • Detect drift and degradation before clients notice it
  • Own incident response for AI services, including root cause analysis and prevention
  • Define and hold SLAs for AI-backed features

Security & Compliance

  • Enforce data residency and handling requirements under Saudi PDPL
  • Manage secrets, access control, and audit trails for models and the data they touch
  • Work through client security reviews and data governance requirements
  • Apply secure practices across the AI supply chain — dependencies, model provenance, prompt and input handling

Integration & Collaboration

  • Work with backend and product teams to expose AI capabilities as reliable services
  • Translate what data scientists and engineers need into durable platform services
  • Integrate AI components with enterprise systems, APIs, and existing client infrastructure
  • Document architecture and operational runbooks properly

Requirements

  • Bachelor's degree in Computer Science, Engineering, or a related field
  • 3–5 years in platform engineering, DevOps, ML engineering, or a similar technical role
  • Strong Python, with the ability to write production code rather than scripts
  • Solid Docker and Kubernetes experience in production, not just locally
  • Hands-on CI/CD and Infrastructure as Code (Terraform, Ansible, or similar)
  • Working knowledge of cloud platforms (AWS, Azure, or GCP) and their managed AI/data services
  • Familiarity with ML concepts and serving frameworks — you don't need to train models, but you need to understand what you're deploying
  • Linux administration competence
  • Practical grasp of security, reliability, and performance in production systems
  • Good communication in English; Arabic is an advantage

Nice to have

  • Experience deploying LLM applications: RAG pipelines, vector databases, inference optimization
  • Model serving frameworks (vLLM, TorchServe, Triton, BentoML, or similar)
  • Observability stack experience (Prometheus, Grafana, OpenTelemetry)
  • Arabic NLP or multilingual model handling
  • On-premises or hybrid deployments where data can't leave the Kingdom
  • Data engineering background (Airflow, dbt, streaming pipelines)
  • Cost optimization experience on GPU workloads
  • Relevant certifications (CKA, cloud ML/architecture certs)

What We Offer

  • Ownership of the platform from the ground up, with your architectural decisions standing
  • Exposure across multiple industries and real production AI use cases
  • A small team where technical judgment carries weight
  • Competitive salary, medical insurance, and annual leave per Saudi labor law



Apply Now!