AI Infrastructure Engineer

Worley-posted 9 months ago
Remote • Houston, TX
Professional, Scientific, and Technical Services
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Worley is a global professional services company of energy, chemicals and resources experts. We partner with customers to deliver projects and create value over the life of their assets. We're bridging two worlds, moving towards more sustainable energy sources, while helping to provide the energy, chemicals and resources needed now. Join the cutting-edge Worley Digital team and help shape the future of AI infrastructure! This is a remote opportunity open to applicants in the U.S., Canada, Latin America, and India (Mumbai or Noida).

  • Collaborate with AI teams to understand computational needs and translate these into infrastructure requirements.
  • Architect secure, optimized and scalable AI infrastructure to support machine learning models and applications.
  • Deploy and manage cloud-based solutions for AI workloads.
  • Optimize data pipelines and storage solutions for efficient data processing and retrieval.
  • Automate deployment and management processes.
  • Troubleshoot and resolve infrastructure-related issues in a timely manner.
  • Stay updated with the latest advancements in AI infrastructure and cloud technologies.
  • Work closely with vendors and Worley teams including FinOps, AI teams and WES operations to monitor, manage, and optimize cloud resources.
  • 4+ years of relevant work experience in solutions design and engineering.
  • Proficient with containerization (Docker, Kubernetes) and cloud service providers (AWS, Azure, GCP).
  • Strong automation development skills, proficient in one or more automation languages (i.e. Ansible, Cloud Formations, Chef, Puppet, Terraform).
  • Bachelor's degree in Computer Science or Software Engineering.
  • Possession of professional cloud certifications.
  • Good knowledge of cloud computing delivery models (IaaS, PaaS, and SaaS) and deployment models related to Public, Private and Hybrid Cloud service.
  • Proficient in Linux/UNIX or Windows environments, including scripting and administration.
  • Familiarity with cloud data services and big data processing tools.
  • Strong background in network architecture and data modelling.
  • Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, Knowledge of routing/switching technologies.
  • Knowledge of monitoring and logging tools (Prometheus, ELK, Grafana, App Insights).
  • Excellent oral and written communication skills in English.
  • Ability to work in a fast-paced, dynamic environment.
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