AI Engineer (Remote)

Posted 15 Hours Ago
Hiring Remotely in United States
Remote
110K-150K Annually
Mid level
Artificial Intelligence • Hardware • Software • Semiconductor
The Role
Design, deploy, and maintain AI-powered applications and scalable cloud infrastructure. Responsibilities include managing AWS or Azure environments, implementing Terraform-based infrastructure, containerizing services with Docker, supporting AI/ML workload scaling, and establishing monitoring, logging, and alerting. The role also involves troubleshooting deployments, automating workflows, collaborating across engineering and data teams, documenting procedures, and following security and reliability best practices.
Summary Generated by Built In
AI Engineer

Experience: 1–5 Years
Salary Range: $110,000 – $150,000 USD per annum
Location: Austin, Texas, United States
Work Arrangement: 100% Fully Remote
Employment Type: Full-Time

Job Summary

We are looking for a talented and motivated AI Engineer with 1–5 years of professional experience to join our growing engineering team.

The ideal candidate should have hands-on experience with cloud platforms such as AWS or Azure, Infrastructure as Code tools like Terraform, containerization technologies such as Docker, and application monitoring solutions.

The successful candidate will help build, deploy, manage, and monitor AI-powered applications and scalable cloud infrastructure. This role is ideal for professionals who are passionate about artificial intelligence, cloud technologies, automation, and modern infrastructure engineering.

This is a fully remote opportunity for candidates currently residing in Austin, Texas, United States.

Key Responsibilities
  • Design, develop, deploy, and maintain AI-powered applications and services.

  • Build and manage cloud infrastructure using AWS or Microsoft Azure.

  • Implement Infrastructure as Code (IaC) solutions using Terraform.

  • Containerize applications and services using Docker.

  • Support the deployment and scaling of AI/ML workloads in cloud environments.

  • Implement monitoring, logging, and alerting solutions to ensure system reliability.

  • Monitor application performance, infrastructure health, and resource utilization.

  • Troubleshoot infrastructure, deployment, and application-related issues.

  • Automate infrastructure provisioning and deployment workflows.

  • Collaborate with AI engineers, software developers, DevOps engineers, and data teams.

  • Follow security, scalability, and cloud infrastructure best practices.

  • Maintain technical documentation and deployment procedures.

  • Participate in code reviews, technical discussions, and continuous improvement initiatives.

Required Technical Skills
  • 1–5 years of professional experience in AI Engineering, Cloud Engineering, DevOps, or a related technical field.

  • Hands-on experience with AWS or Microsoft Azure.

  • Practical knowledge of Terraform and Infrastructure as Code.

  • Experience with Docker and containerization.

  • Understanding of cloud infrastructure, networking, and deployment concepts.

  • Knowledge of monitoring, logging, and alerting tools.

  • Understanding of application deployment and troubleshooting.

  • Familiarity with CI/CD pipelines and automation practices.

  • Basic understanding of AI/ML application deployment and cloud integration.

  • Strong analytical, troubleshooting, and problem-solving skills.

Preferred Qualifications
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

  • Familiarity with Kubernetes and container orchestration.

  • Exposure to monitoring tools such as Prometheus, Grafana, Datadog, or CloudWatch.

  • Knowledge of Python or scripting languages.

  • Familiarity with Git and version control systems.

  • Understanding of cloud security, IAM, and access management.

  • Exposure to machine learning frameworks and AI deployment workflows.

  • Familiarity with serverless computing and cloud-native architectures.

  • Understanding of Agile/Scrum development methodologies.

Compensation & Benefits
  • Annual Salary: $110,000 – $150,000 USD.

  • Full-time employment opportunity.

  • 100% fully remote work arrangement.

  • Opportunities for professional growth and technical development.

  • Exposure to modern AI and cloud technologies.

  • Collaborative and flexible remote working environment.

  • Opportunities to work on innovative AI-powered projects.

Final compensation will depend on relevant experience, technical expertise, qualifications, and overall skills.

Location & Work Requirements
  • This is a 100% fully remote position.

  • Candidates must currently reside in Austin, Texas, United States.

  • Candidates must be authorized to work in the United States.

  • Must be comfortable collaborating with distributed teams during US business hours.

  • Strong written and verbal communication skills are required.

  • Ability to work independently and collaboratively in a remote environment.

What We're Looking For
  • A passionate technology professional interested in AI and cloud engineering.

  • Strong understanding of cloud infrastructure and automation.

  • Ability to troubleshoot and resolve technical challenges.

  • Attention to detail and commitment to system reliability.

  • Strong communication and teamwork skills.

  • Willingness to learn emerging AI and cloud technologies.

  • Ability to manage priorities and deliver high-quality solutions.

How to Apply

If you are passionate about Artificial Intelligence, AWS/Azure, Terraform, Docker, and cloud infrastructure, we would love to hear from you!

Whether you have experience deploying AI applications or managing cloud environments, this is an exciting opportunity to grow your career in AI Engineering.

Apply now and become part of our growing engineering team!

Skills Required

  • 1-5 years of professional experience in AI Engineering, Cloud Engineering, DevOps, or a related technical field
  • Hands-on experience with AWS or Microsoft Azure
  • Practical knowledge of Terraform and Infrastructure as Code
  • Experience with Docker and containerization
  • Understanding of cloud infrastructure, networking, and deployment concepts
  • Knowledge of monitoring, logging, and alerting tools
  • Understanding of application deployment and troubleshooting
  • Familiarity with CI/CD pipelines and automation practices
  • Basic understanding of AI/ML application deployment and cloud integration
  • Strong analytical, troubleshooting, and problem-solving skills
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
  • Familiarity with Kubernetes and container orchestration
  • Exposure to Prometheus, Grafana, Datadog, or CloudWatch
  • Knowledge of Python or scripting languages
  • Familiarity with Git and version control systems
  • Understanding of cloud security, IAM, and access management
  • Exposure to machine learning frameworks and AI deployment workflows
  • Familiarity with serverless computing and cloud-native architectures
  • Understanding of Agile/Scrum development methodologies
  • Authorization to work in the United States
  • Strong written and verbal communication skills
  • Ability to work independently and collaboratively in a remote environment
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The Company
5 Employees
Year Founded: 2018

What We Do

EdgeQ develops 5G systems-on-chip for wireless infrastructure, combining connectivity and AI in a software-customizable, programmable platform. Its technology supports configurable 5G services and Open RAN deployments for enterprises, telecom operators and cloud providers, including base-station and edge-network use cases. The company’s mission is to make 5G more accessible through software-driven customization and bring cloud computing and data processing closer to where connectivity and data are used.

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