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We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

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We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

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Senior Machine Learning Engineer
Location: Abu Dhabi, UAE - Remote Global
Type: Contract

Role Summary
We are seeking a Senior Machine Learning Engineer to lead the development and deployment of advanced AI models. In this role, you will be responsible for the end-to-end lifecycle of machine learning systems, from architectural design and data preprocessing to model training, optimization, and production deployment.

You will work at the intersection of generative AI and traditional machine learning, building the engines that power automated requirements engineering via LLMs and predictive risk scoring and demand forecasting solutions. Operating within a structured "Sprint Zero" to "Stage Gate" delivery model, you will ensure models are not just accurate, but also robust, explainable, and deployable within strict security environments.

Key Responsibilities

LLM & NLP PipelinesRegulation Parsing: Design and fine-tune Large Language Model (LLM) pipelines to interpret complex regulatory texts (e.g., military standards, building codes) and extract structured rules.Rule Formalization: Convert natural language requirements into computer-processable formats (e.g., logic tuples) that can be executed by downstream compliance engines.Semantic Search: Implement RAG (Retrieval-Augmented Generation) architectures to enable semantic querying of technical documentation and historical project data.Prompt Engineering: Optimize prompt strategies (few-shot learning, chain-of-thought) to improve model performance on domain-specific tasks without extensive retraining. Predictive & Analytical ModelsForecasting Engines: Develop time-series forecasting models to predict material demand and spend categories, integrating internal ERP data with external market signals.Risk Scoring: Build classification and anomaly detection models to assess supplier risk profiles based on financial health, delivery performance, and geopolitical factors.Optimization Algorithms: Design algorithms for multi-objective optimization (e.g., balancing cost vs. lead time vs. risk) to support procurement decision-making. MLOps & ProductionizationModel Deployment: Containerize models using Docker/Kubernetes and deploy them into secure, on-premises inference environments.Pipeline Orchestration: Build automated training and inference pipelines using tools like Kubeflow or MLflow to ensure reproducibility and scalability.Performance Optimization: Optimize model inference latency and resource usage (e.g., quantization, distillation) to run efficiently on available hardware.Monitoring & Retraining: Implement monitoring systems to track model drift and performance in production, establishing feedback loops for continuous improvement.

Technical Requirements

Core ML/AI: Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy).NLP & GenAI: Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain).MLOps: Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow).Data Handling: Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data.Algorithm Design: Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations.

Professional Qualifications

Experience: 5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments.Domain Adaptability: Ability to quickly learn and apply ML techniques to specialized domains like defense engineering, supply chain, or construction.Structured Delivery: Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements.Collaboration: Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.

Why This Role?

You will be building the intelligence that drives critical national infrastructure. Your models will not just generate text or predictions; they will directly influence the design of complex systems and the resilience of supply chains. If you are ready to apply advanced ML to tangible, high-stakes problems in a rigorous engineering environment, this role is for you.

GCS is acting as an Employment Business in relation to this vacancy.

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We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

Read less

We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

Read less

We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

Read less

We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

Read less

Cloud Engineer - Fully Remote | 6-Month Contract

An exciting opportunity is available for a Cloud Engineer to join a high-performing Platform Engineering team on a 6-month contract basis.

This is a hands-on role focused on building and improving cloud infrastructure through Infrastructure as Code, automation, CI/CD and DevOps practices. You'll work closely with cloud and platform engineering teams to deliver secure, scalable and reusable cloud services that support application and development teams across the organisation.

Key Responsibilities

Build and maintain cloud infrastructure using IaC tools such as Terraform, CloudFormation or Bicep.Develop and maintain CI/CD pipelines to automate infrastructure and application deployments.Automate cloud provisioning, configuration and operational processes.Implement cloud infrastructure in line with security, governance and compliance requirements.Work with platform and cloud teams to deliver scalable and standardised cloud services.Support monitoring, observability and troubleshooting of cloud environments.distributed engineering team.

Desirable

AWS certifications.Experience with security automation or policy-as-code.Experience working within enterprise cloud environments.

GCS is acting as an Employment Business in relation to this vacancy.

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We are seeking an experienced DevOps Architect to lead the design, automation, and optimization of cloud infrastructure and platform engineering solutions. This role will partner closely with engineering teams to establish architectural standards, improve system reliability, and drive scalable cloud initiatives.

Key ResponsibilitiesDesign and implement scalable, highly available cloud infrastructure.Define architecture standards, best practices, and technical roadmaps.Build, optimize, and support Kubernetes-based platforms.Develop Infrastructure as Code (IaC) solutions using Terraform.Drive automation initiatives to improve engineering efficiency.Enhance monitoring, observability, and platform reliability.Lead architecture reviews and provide technical guidance across teams.Create and maintain technical documentation and architectural decision records (ADRs).Required Qualifications10+ years of experience in DevOps, Platform Engineering, Cloud Engineering, Site Reliability Engineering (SRE), Infrastructure Engineering, or Cloud Architecture.Strong experience with Google Cloud Platform (GCP) and/or AWS.Deep expertise in Kubernetes, including large-scale production environments.Advanced experience with Terraform and Infrastructure as Code practices.Strong programming and automation skills in Python and Bash (Go is a plus).Solid Linux systems administration and troubleshooting experience.Experience designing highly available, multi-region, and disaster recovery solutions.Proven ability to establish architecture standards and influence technical direction across teams.Preferred Technologies

GCP, AWS, Kubernetes, Terraform, Python, Bash, Go, Linux, Prometheus, Grafana, ELK Stack, Jenkins, GitLab CI/CD, ArgoCD, and GitOps.

This is an excellent opportunity for a hands-on technical leader who enjoys solving complex infrastructure challenges, driving automation, and building reliable cloud platforms at scale.

GCS is acting as an Employment Business in relation to this vacancy.

Read less

GCS is acting as an Employment Business in relation to this vacancy.

Read less