onsite
Applied AI Platform & DevOps Engineer - CohnReznick
Devops Engineer
Design, build, and operate AI‑powered platforms on cloud infrastructure, automating deployment pipelines and ensuring scalable, secure environments for generative AI solutions.
About the role
Key Responsibilities
- Architect and implement end‑to‑end AI platforms that support generative AI workloads, leveraging cloud services and container orchestration.
- Develop and maintain CI/CD pipelines using tools such as GitHub Actions, Jenkins, or Azure DevOps to automate model training, testing, and deployment.
- Containerize Python‑based AI services with Docker and orchestrate them on Kubernetes clusters, ensuring high availability and performance.
- Manage infrastructure as code with Terraform or CloudFormation to provision and scale resources on AWS.
- Collaborate with data scientists and software engineers to integrate machine‑learning models into production, monitoring performance and cost.
- Implement security best practices, logging, and monitoring to safeguard AI assets and comply with governance standards.
Requirements
- 3+ years of experience in DevOps or platform engineering, preferably with AI/ML workloads.
- Proficiency in Python programming and container technologies (Docker, Kubernetes).
- Hands‑on experience with AWS services (ECS/EKS, S3, Lambda) and infrastructure‑as‑code tools (Terraform, CloudFormation).
- Strong knowledge of CI/CD pipelines, automated testing, and release management.
- Familiarity with machine‑learning concepts, model lifecycle, and generative AI frameworks (e.g., PyTorch, TensorFlow).
Skills
pythondockerkubernetesawscicdterraformmachine learninggenerative ai