Enterprise AI Engineer I

Expedia Expedia · Hospitality · Gurgaon, India

Early-career Enterprise AI Engineer I to support the design, deployment, and operation of cloud-based infrastructure and AI-adjacent systems. The role involves working on well-defined tasks within larger projects, debugging and automating infrastructure and services, and learning about scale and reliability in cloud environments.

What you'd actually do

  1. Support the day‑to‑day operation of cloud and on‑prem infrastructure and services, following established runbooks and standards.
  2. Assist with implementing and validating engineering designs and changes in production environments.
  3. Debug and troubleshoot lower‑complexity systems and infrastructure issues, collecting data and escalating when needed.
  4. Write simple scripts and tools (e.g. in Python or PowerShell) to automate routine tasks and basic troubleshooting steps.
  5. Help maintain documentation, procedures and configuration for systems and services.

Skills

Required

  • 0-2 years of experience in technical, IT, infrastructure, systems, or platform engineering
  • Bachelor’s degree or equivalent practical experience in a relevant field
  • Experience contributing to the implementation and deployment of an engineering design
  • Experience working as part of a team to build and support a product or project in public or hybrid cloud infrastructure (AWS, Azure, GCP)
  • Familiarity with one programming or scripting language (Python, PowerShell)
  • Ability to understand basic programming concepts and control flow
  • Able to configure, operate, and automate cloud IaaS resources with guidance
  • Understanding of lower-complexity systems
  • Basic knowledge of operating systems, system testing tools, and system administration concepts
  • General AI literacy with exposure to LLMs and RAG
  • Familiarity with Agile software delivery practices and tools (Jira)
  • Clear communication skills
  • Ability to collaborate effectively with technical and non-technical stakeholders
  • Comfortable following standard processes and procedures

Nice to have

  • Experience with infrastructure services and tooling (monitoring, logging, CI/CD, configuration management)
  • Exposure to AI/ML or automation platforms (model serving, feature stores, workflow orchestration)
  • Experience writing code to automate troubleshooting steps or common operational tasks
  • Understanding of system and technology integration concepts
  • Experience performing routine systems administration tasks
  • Demonstrated interest in emerging technology trends in cloud, AI and infrastructure
  • Desire to build deeper expertise in a specific engineering area
  • Proven ability to collaborate with peers
  • Ask thoughtful questions
  • Seek knowledge from subject matter experts

What the JD emphasized

  • 0–2 years of experience in technical, IT, infrastructure, systems, or platform engineering (including internships or projects)
  • Bachelor’s degree or equivalent practical experience in a relevant field; technical degree preferred
  • Experience contributing to the implementation and deployment of an engineering design into a production or pre‑production environment
  • Experience working as part of a team to build and support a product or project in public or hybrid cloud infrastructure (e.g. AWS, Azure, GCP)
  • Familiarity with one programming or scripting language (e.g., Python, PowerShell) and ability to understand basic programming concepts and control flow, and write and explain a simple function or script
  • Able to configure, operate, and automate cloud IaaS resources with guidance (e.g., compute, storage, networking, IAM)
  • Understanding of lower‑complexity systems and how individual functions or components fit into a broader team project
  • Basic knowledge of operating systems, system testing tools, and system administration concepts
  • General AI literacy with exposure to LLMs and retrieval‑augmented generation (RAG), and understanding beyond simple prompting (e.g. basic model capabilities, limitations, and safe use)
  • Familiarity with Agile software delivery practices and tools such as Jira (e.g., working with boards, tickets, and sprints)
  • Clear, concise communication skills, with the ability to collaborate effectively with both technical and non‑technical stakeholders
  • Comfortable following standard processes and procedures, collecting information to understand problems, researching known solutions, and implementing prescribed steps to resolution