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Emerging Technology Services Engineer
Job in
Riyadh, Riyadh Region, Saudi Arabia
Listed on 2026-07-13
Listing for:
Datamatics Technologies
Full Time, Seasonal/Temporary
position Listed on 2026-07-13
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Job Title: Emerging Technology Services Engineer
Experience: 6–11 Years
Location: Riyadh (Onsite)
Employment Type: Full-Time
We are seeking an experienced Emerging Technology Services Engineer with 6–11 years of experience to drive innovation initiatives, evaluate emerging technologies, and develop proof-of-concepts (PoCs) that support business transformation. The ideal candidate will have hands‑on experience in AI/ML experimentation, cloud-native technologies, automation, orchestration, and innovation enablement, with the ability to translate new technologies into scalable business solutions.
Key Responsibilities- Research, evaluate, and implement emerging technologies to address business and technical challenges.
- Design, develop, and deliver AI/ML Proof of Concepts (PoCs) to validate new ideas and technologies.
- Build cloud-native solutions that are scalable, resilient, and secure.
- Design and implement automation and orchestration solutions to improve operational efficiency.
- Collaborate with engineering, architecture, product, and business teams to identify innovation opportunities.
- Assess technology trends and recommend adoption strategies aligned with organizational objectives.
- Develop prototypes and pilot solutions to demonstrate business value.
- Document solution architectures, technical findings, and best practices.
- Mentor technical teams on emerging technologies and innovation frameworks.
- Participate in architecture reviews and technology governance initiatives.
- Hands‑on experience with AI/ML PoC development
. - Experience with machine learning model development, evaluation, and deployment.
- Familiarity with Generative AI, Large Language Models (LLMs), and AI frameworks is preferred.
- Strong experience with cloud-native exploration and solution development
. - Hands‑on experience with AWS or Microsoft Azure or Google Cloud Platform (GCP).
- Experience with microservices, containers, and Kubernetes is preferred.
- Strong experience in automation and orchestration using modern enterprise tools and scripting frameworks.
- Experience building automated deployment, provisioning, and operational workflows.
- Knowledge of Infrastructure as Code (IaC) is an advantage.
- Experience driving innovation enablement through technology assessments, rapid prototyping, and pilot implementations.
- Ability to evaluate emerging technology trends and recommend enterprise adoption strategies.
- Experience working with innovation labs, R&D initiatives, or digital transformation programs is preferred.
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
- 6–11 years of professional experience in software engineering, cloud technologies, AI/ML, or emerging technology initiatives.
- Strong analytical, problem‑solving, and solution design capabilities.
- Excellent communication and stakeholder management skills.
- Experience working in Agile/Scrum environments.
- Experience with Dev Ops and CI/CD pipelines.
- Knowledge of API integrations and event-driven architectures.
- Exposure to data engineering and analytics platforms.
- Familiarity with cybersecurity best practices for cloud-native applications.
- Cloud certifications and AI/ML certifications are a plus.
- Artificial Intelligence: AI/ML PoC development and Generative AI or Large Language Models (LLMs)
- Cloud: AWS or Microsoft Azure or Google Cloud Platform (GCP)
and cloud-native architectures - Automation: Automation and orchestration and Infrastructure as Code (Preferred)
- Containers: Docker and Kubernetes
- Dev Ops: CI/CD pipelines and Git-based version control
- Innovation: Innovation enablement and rapid prototyping and technology evaluation and proof-of-concept development
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