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- Tasks: Design and automate cloud infrastructure, manage CI/CD pipelines, and ensure system reliability.
- Company: AI71 is an innovative research team focused on impactful AI solutions for knowledge workers.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and mentorship.
- Why this job: Join a high-growth team where you can shape technology and culture from day one.
- Qualifications: Bachelor’s degree or equivalent experience; 3+ years in DevOps/SRE; cloud and Kubernetes expertise required.
- Other info: Ideal for builders who thrive in fast-paced, early-stage tech environments.
The predicted salary is between 54000 - 84000 ÂŁ per year.
Location: Abu Dhabi
Company: AI71
About Us
AI71 is an applied research team dedicated to building responsible and impactful AI agents that empower knowledge workers. We work closely with our industry partners and leverage cutting-edge research from the Technology Innovation Institute (TII) to develop AI products that drive transformative change.
About the Role
As a DevOps Engineer at AI71 you will own the pipelines, platforms, and processes that let our researchers ship AI from notebook to production at lightning speed and enterprise scale. You’ll design and automate cloud‑native infrastructure, champion CI/CD best practices, and ensure our GenAI services run reliably, securely, and cost‑effectively across staging, test, and high‑availability production environments. This is an early‑stage, high‑growth environment—perfect for builders who like green‑field architecture, rapid iteration, and the chance to shape both culture and tech stack from day one.
Key Responsibilities
- Design & Build Cloud Infrastructure: Architect scalable, secure, and cost‑optimized Kubernetes‑based environments (EKS/GKE/AKS or on‑prem k8s). Codify infrastructure with Terraform, Pulumi, or similar IaC, implementing GitOps‑style workflows.
- End‑to‑End CI/CD Automation: Create and maintain CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or Argo Workflows) for containerized microservices, ML model training, and inference workloads. Integrate automated testing, security scans, and policy checks into the release process.
- Observability & Reliability Engineering: Implement comprehensive monitoring, logging, and tracing stacks (Prometheus/Grafana, Loki, ELK, OpenTelemetry). Define SLOs/SLA dashboards; lead incident response, root‑cause analysis, and post‑mortems.
- Security & Compliance: Embed DevSecOps practices—secrets management, container image hardening, zero‑trust networking, vulnerability management, and compliance automation (ISO 27001, SOC 2).
- Collaborate with ML/AI Teams: Package and deploy large‑language‑model (LLM) training jobs on distributed GPU clusters (Slurm, Ray, Kubeflow, or AWS SageMaker). Optimize model‑serving (Triton, vLLM, TorchServe) for low‑latency, high‑throughput inference.
- Cost & Performance Optimization: Track cloud spend, right‑size resources, and introduce autoscaling strategies (Karpenter, Cluster‑Autoscaler, HPA/VPA). Champion FinOps best practices and forecasting.
- Culture & Process: Mentor engineers on DevOps fundamentals. Establish runbooks, playbooks, and robust documentation to support rapid onboarding and knowledge sharing.
Required Qualifications
- Bachelor’s degree in computer science, Engineering, or related field (or equivalent practical experience).
- 3+ years of hands‑on DevOps/SRE experience building and operating production systems.
- Proficiency with at least one major cloud provider (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker).
- Strong skills in Infrastructure‑as‑Code (Terraform, CloudFormation, Pulumi, or CDK).
- Experience implementing CI/CD for microservices or ML pipelines.
- Solid understanding of networking, Linux, and security fundamentals.
Preferred Qualifications
- Experience supporting GPU‑accelerated workloads or MLOps/LLMOps platforms.
- Familiarity with service mesh (Istio, Linkerd) and event‑driven architectures (Kafka, Pub/Sub).
- Knowledge of distributed storage systems (Ceph, MinIO, S3) and artifact registries.
- Certifications: CKA/CKAD, AWS DevOps Engineer Professional, or equivalent.
- Track record in early‑stage or high‑growth tech environments.
- Excellent communication skills; ability to partner with researchers, backend engineers, and product stakeholders.
Senior DevOps Engineer [UAE Based] employer: AI71
Contact Detail:
AI71 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior DevOps Engineer [UAE Based]
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Kubernetes, Terraform, and CI/CD pipelines. Having hands-on experience or projects showcasing these skills can set you apart during discussions.
✨Tip Number 2
Network with current or former employees of AI71 or similar companies. Engaging with them on platforms like LinkedIn can provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss your experience with cloud-native infrastructure and DevSecOps practices. Be ready to share specific examples of how you've implemented security measures and optimised costs in previous roles.
✨Tip Number 4
Showcase your ability to mentor and lead by preparing examples of how you've supported team members in understanding DevOps fundamentals. This aligns well with the role's emphasis on culture and process development.
We think you need these skills to ace Senior DevOps Engineer [UAE Based]
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in DevOps, particularly with cloud providers and container orchestration. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and DevOps. Mention specific projects or experiences that align with the responsibilities listed in the job description, such as CI/CD automation or cloud infrastructure design.
Showcase Technical Skills: In your application, emphasise your proficiency with tools like Terraform, Kubernetes, and CI/CD pipelines. Provide examples of how you've used these technologies in past roles to solve problems or improve processes.
Highlight Collaboration Experience: Since the role involves working closely with ML/AI teams, include examples of past collaborations. Discuss how you’ve partnered with engineers or researchers to achieve common goals, showcasing your communication skills.
How to prepare for a job interview at AI71
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with cloud providers and container orchestration. Highlight specific projects where you've implemented CI/CD pipelines or worked with Infrastructure-as-Code tools like Terraform.
✨Demonstrate Problem-Solving Abilities
Expect scenario-based questions that assess your ability to troubleshoot and optimise systems. Prepare examples of past incidents you've managed, focusing on your approach to root-cause analysis and incident response.
✨Understand the Company Culture
Research AI71's mission and values. Be ready to discuss how your personal work ethic aligns with their focus on responsible AI and collaboration with industry partners. This shows your genuine interest in the role.
✨Prepare Questions for Them
Have insightful questions ready about their current tech stack, team dynamics, and future projects. This not only demonstrates your enthusiasm but also helps you gauge if the company is the right fit for you.
