Senior DevOps Engineer

Socket.dev; Maryland; On-site; USD 140,000 - 200,000; Full time

Job summary

Socket.dev seeks a highly experienced Senior DevOps Engineer to lead deployment of AI infrastructure and workflows in enterprise environments.

You will design cloud infrastructure in AWS/Azure, build CI/CD pipelines, and implement Docker/Kubernetes across teams, while ensuring scalable AI model lifecycle management.

Candidates should have 12+ years in DevOps, strong IaC skills with Terraform/Ansible, and TS/SCI with polygraph is required.

Qualifications

• 12+ years of experience with DevOps in enterprise environments.
• Advanced proficiency in DevOps principles and practices.
• Expertise in Docker and Kubernetes containerization.
• Proven experience architecting and managing CI/CD pipelines.
• Extensive AI model lifecycle management experience.
• Familiarity with AWS and Azure for infra deployment.
• Experience with monitoring/logging tools such as Prometheus, Grafana, ELK.
• Excellent communication and cross-functional collaboration.
• Knowledge of IaC tools like Terraform and Ansible.
• Understanding of ML concepts for infrastructure implications.

Responsibilities

• Design, implement, and maintain infrastructure for enterprise AI apps in AWS/Azure.
• Develop and optimize AI model development, deployment, and maintenance workflows.
• Architect and manage CI/CD pipelines for AI models and apps.
• Implement containerization with Docker and Kubernetes.
• Ensure efficient AI model lifecycle management including versioning and scaling.
• Collaborate with AI/ML engineers and data scientists to streamline deployment.
• Oversee performance, security, and scalability of AI infrastructure.
• Continuously research and adopt new DevOps tools and practices.

Skills

DevOps principles

Docker

Kubernetes

CI/CD pipelines

Cloud platforms AWS/Azure

Monitoring & Logging

Communication

Education

B.S. in a relevant technical field

M.S. in a relevant technical field

Tools

Terraform

Ansible

Docker

Kubernetes

Prometheus

Grafana

ELK stack

Job description

Overview

Possesses and applies a comprehensive knowledge across key tasks and high impact assignments. Plans and leads major technology assignments. Evaluates performance results and recommends major changes affecting short-term project growth and success. Functions as a technical expert across multiple project assignments. May supervise others.

Position Overview

We are seeking a highly experienced and technically proficient Senior DevOps Engineer to play an integral role in our team, focusing on deploying infrastructure and engineering workflows and processes to support enterprise AI rollouts. This position requires deep expertise in DevOps principles, including containerization, CI/CD pipeline architecture, and AI model lifecycle management. The ideal candidate will be adept at ensuring robust, scalable, and efficient deployment and maintenance of AI applications at an enterprise scale.

What You’ll Be Doing

• Design, implement, and maintain robust infrastructure for enterprise AI applications in cloud environments (AWS, Microsoft Azure)
• Develop and optimize engineering workflows and processes to support AI model development, deployment, and maintenance.
• Architect and manage CI/CD pipelines for continuous integration and continuous delivery of AI models and applications.
• Implement and manage containerization solutions using technologies like Docker and Kubernetes.
• Ensure efficient AI model lifecycle management, including versioning, monitoring, and scaling.
• Collaborate with AI/ML engineers and data scientists to streamline deployment processes and optimize resource utilization.
• Oversee system performance, security, and scalability of AI infrastructure.
• Continuously research and implement new DevOps tools and practices to enhance efficiency.

Required Experience

• B.S. in a relevant technical field with 12 years of experience, or M.S. in a relevant technical field with 10 years of experience.
• Advanced proficiency in DevOps principles and practices.
• Demonstrated expertise in containerization using Docker and Kubernetes.
• Proven experience in architecting and managing CI/CD pipelines.
• Extensive experience with AI model lifecycle management and maintenance.
• Familiarity with cloud platforms (AWS, Microsoft Azure) for infrastructure deployment and management.
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
• Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.
• Ability to translate complex technical concepts into actionable engineering solutions.

Desired Skills

• Experience with infrastructure as code (IaC) tools (e.g., Terraform, Ansible).
• Understanding of machine learning concepts and their implications for infrastructure.
• Continuous learning mindset to stay abreast of cutting-edge DevOps and AI advancements.

TS/SCI with polygraph is required.