Devops Engineer- Dallas, TX

The DevOps Engineer will play a critical role in bridging development, infrastructure, and operations to enable reliable, scalable, and secure delivery of modern cloud-native and AI-powered platforms. This role requires a strong combination of deep technical expertise in cloud infrastructure, automation, and CI/CD practices, along with the ability to collaborate effectively across engineering, product, and platform teams.

You will be responsible for defining and implementing DevOps strategies, optimizing infrastructure, driving automation, and ensuring high availability and performance of systems in production. The role also involves supporting AI/ML platforms by enabling robust MLOps practices and ensuring seamless deployment, monitoring, and scaling of applications and services.

Key Responsibilities:

Infrastructure Design: Design, implement, and manage scalable, secure, and highly available cloud infrastructure across AWS, Azure, or GCP

Automation & CI/CD: Build and maintain robust CI/CD pipelines for continuous integration, testing, and deployment using tools like Jenkins, GitLab CI, or GitHub Actions

Cloud & Platform Engineering: Develop and manage cloud-native architectures, ensuring efficient resource utilization, scalability, and reliability

Containerization & Orchestration: Implement and manage containerized environments using Docker and orchestrate them with Kubernetes

Monitoring & Observability: Establish monitoring, logging, and tracing systems to ensure system reliability and enable real-time diagnostics

Infrastructure as Code (IaC): Define and manage infrastructure using tools like Terraform, CloudFormation, or ARM templates

Performance Optimization: Optimize infrastructure and deployment pipelines for performance, scalability, and cost-efficiency

MLOps Enablement: Support deployment and lifecycle management of ML/AI models, including versioning, monitoring, and scaling

Required Skills & Qualifications:

• 10+ years of experience in DevOps, infrastructure engineering, or platform engineering roles
• Strong experience with cloud platforms (AWS, Azure, or GCP) and cloud-native architectures
• Expertise in CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and automation practices
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes)
• Strong knowledge of Infrastructure as Code (Terraform, CloudFormation, ARM templates)
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack, Datadog, etc.)
• Proficiency in scripting languages (Python, Bash, Shell scripting)
• Experience in microservices architecture and distributed systems
• Strong understanding of networking, security, and system design principles
• Experience with databases and storage systems (SQL, NoSQL, caching systems like Redis)
• Familiarity with MLOps practices and supporting AI/ML workloads in production
• Experience in managing high-availability systems, incident management, and disaster recovery
• Strong understanding of version control systems (Git)
• Ability to collaborate across teams and drive operational excellence