Remote AI/ML & GenAI Engineer — RAG & MLOps

Jobgether; Saudi Arabia; On-site; SAR 375,000 - 450,000; Full time

Benefits offered by this job

Competitive salary

Remote work

GenAI projects

Job summary

Jobgether seeks an AI/ML & Forward Deployed Engineer based in Saudi Arabia to design, deploy, and scale GenAI solutions from concept to production. You will work across LLMs, RAG pipelines, embeddings, and REST/gRPC services, building secure, observable AI systems with strong governance.

You will collaborate with stakeholders to translate business needs into practical AI solutions, maintaining CI/CD pipelines, and ensuring production reliability with MLOps/LLMOps best practices.

Qualifications

• 8+ years of professional software engineering experience.
• Hands-on ML/AI engineering.
• Advanced Python development with DL/ML techniques.
• Experience with NLP, forecasting, classification, regression, anomaly detection.
• GenAI apps with LLMs and RAG architectures.
• Embeddings, retrieval tuning, reranking, prompt engineering, AI evaluation methodologies.
• MLOps/LLMOps across the AI lifecycle.
• Docker, Kubernetes, and CI/CD for production deployments.
• REST and gRPC APIs and event-driven services.
• Model monitoring, drift detection, lifecycle management.
• Data quality, governance, security, RBAC, encryption, audit trails.
• Stakeholder collaboration to translate challenges into AI solutions.
• Strong problem-solving, analytical, communication & collaboration.

Responsibilities

• Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.
• Build and optimize ML models and applications covering deep learning, NLP, forecasting, classification, regression, and anomaly detection use cases.
• Develop production-grade GenAI applications using LLMs, RAG pipelines, embeddings, retrieval optimization, reranking, and prompt engineering.
• Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and performance.
• Build scalable AI services and integrations using REST and gRPC APIs as well as event-driven architectures.
• Establish and maintain MLOps and LLMOps practices covering deployment, automation, versioning, monitoring, and lifecycle management.
• Containerize and orchestrate AI applications using Docker and Kubernetes and integrate them into robust CI/CD pipelines.
• Implement model monitoring, drift detection, performance tracking, and processes for continuous model improvement.
• Ensure AI solutions meet enterprise requirements for data quality, governance, security, RBAC, encryption, and auditability.
• Collaborate with business and technical stakeholders to understand requirements, identify opportunities for AI adoption, and translate them into effective technical solutions.
• Support solutions through production operations, troubleshooting, optimization, and ongoing improvements.
• Apply strong engineering practices to ensure AI systems are scalable, secure, observable, maintainable, and aligned with business objectives.

Skills

Python

ML Engineering

NLP

GenAI

LLMs

MLOps

LLMOps

Docker

Kubernetes

REST APIs

gRPC

CI/CD

Security & RBAC

Data Governance

Tools

Docker

Kubernetes

CI/CD

Job description

Jobgether seeks an AI/ML & Forward Deployed Engineer based in Saudi Arabia to design, deploy, and scale GenAI solutions from concept to production. You will work across LLMs, RAG pipelines, embeddings, and REST/gRPC services, building secure, observable AI systems with strong governance.

You will collaborate with stakeholders to translate business needs into practical AI solutions, maintaining CI/CD pipelines, and ensuring production reliability with MLOps/LLMOps best practices.