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.
