AI DevOps Engineer

TechDigital Group; Plano (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

TechDigital Group is seeking an AI DevOps Engineer to integrate ML models into production, manage cloud and on-prem infrastructure, and automate deployment pipelines. You will collaborate with data scientists, software engineers, and product managers to deliver AI-powered solutions.

The role emphasizes scalable, secure AI systems, monitoring, and documentation, with hands-on work in Python, cloud platforms, and IaC tools. Plano, TX-based on-site position preferred.

Qualifications

• Proficient in Python; Bash and/or Java familiarity is helpful.
• Experience deploying AI/ML workloads on cloud platforms.
• Understanding of ML models, data pipelines, and AI frameworks.
• Hands-on with CI/CD tools, containerization, and IaC.
• Strong problem-solving and cross-functional collaboration skills.
• Excellent communication for technical and non-technical stakeholders.
• 10+ years of experience in AI/DevOps roles.

Responsibilities

• AI/ML deployment and operations in production environments.
• Provision and manage cloud and on-prem infrastructure, including GPU servers.
• Develop and maintain CI/CD pipelines for AI apps.
• Automate tasks and deployments with scripting (Python preferred).
• Collaborate with engineers, data scientists, and product teams.
• Implement monitoring, logging, and security best practices.
• Create technical docs and train users on AI systems.

Skills

Python programming

Bash familiarity

Java familiarity

Cloud platforms

ML/AI knowledge

CI/CD tooling

Communication

Problem-solving

Tools

Docker

Kubernetes

Terraform

Ansible

Jenkins

GitLab CI

Job description

An AI DevOps Engineer is responsible for integrating artificial intelligence and machine learning models into operational environments, managing cloud infrastructure, and automating deployment pipelines. This role ensures AI solutions are reliable, scalable, and secure, while collaborating with data scientists, software engineers, and business stakeholders to deliver AI-powered products effectively

Key Responsibilities

• AI/ML Deployment and Operations: Deploy, monitor, and maintain AI and ML models in production environments, ensuring performance and reliability
• Infrastructure Management: Provision, configure, and maintain cloud and on-premises infrastructure, including GPU servers and high-performance computing resources
• CI/CD Pipeline Development: Build and manage continuous integration and continuous deployment pipelines for AI applications
• Automation and Scripting: Automate repetitive tasks, infrastructure provisioning, and model deployment using scripting languages like Python
• Collaboration: Work closely with cross-functional teams, including engineers, data scientists, and product managers, to design and implement AI solutions
• Monitoring and Security: Implement monitoring, logging, and security best practices to ensure AI systems operate safely and efficiently
• Documentation and Training: Create technical documentation and provide training to end-users or team members on AI system usage and maintenance

Required Skills and Qualifications

• Programming: Proficiency in Python is essential; familiarity with other languages like Bash or Java is beneficial
• Cloud Platforms: Experience with cloud services such as AWS, Azure, or Google Cloud for AI deployment
• AI/ML Knowledge: Understanding of machine learning models, data pipelines, and AI frameworks (e.g., TensorFlow, PyTorch) is highly desirable
• DevOps Tools: Experience with CI/CD tools (Jenkins, GitLab CI), containerization (Docker, Kubernetes), and infrastructure-as-code (Terraform, Ansible) is important
• Problem-Solving: Ability to troubleshoot complex system issues and optimize AI workflows
• Communication: Strong collaboration and communication skills to work with technical and non-technical stakeholders

Years of Experience

10.00 Years of Experience