DevOps Engineer Lead

Roles & Responsibilities

About the Role:

We are seeking an experienced DevOps Lead with a strong background in AI/ML workflows to guide our platform’s infrastructure, automation, and deployment initiatives. In this role, you will oversee end-to-end application delivery pipelines—including those supporting AI and machine learning solutions—and collaborate closely with cross-functional teams to ensure scalability, performance, and security. This position is ideal for a hands-on leader who excels at translating complex technical challenges into streamlined processes and solutions.

Key Responsibilities

• Lead DevOps Strategy & Roadmap: Define and implement the overarching DevOps strategy, ensuring alignment with the organization’s business objectives and AI program goals.
• Infrastructure Management: Oversee the design and deployment of cloud-based infrastructure (AWS, Azure, or GCP) for both traditional applications and AI/ML pipelines, leveraging infrastructure-as-code tools (Terraform, CloudFormation, etc.).
• CI/CD & Automation: Architect, maintain, and optimize CI/CD pipelines (Jenkins, GitLab, or GitHub Actions) to streamline code deployments, testing, and AI model releases.
• Containerization & Orchestration: Develop and maintain containerized services using Docker or similar technologies, orchestrating them with Kubernetes or other container orchestration platforms.
• MLOps Implementation: Collaborate with data scientists and ML engineers to design and maintain machine learning pipelines, model training workflows, and model serving platforms with a focus on scalability, reliability, and security.
• Monitoring & Observability: Establish robust monitoring, logging, and alerting solutions (Prometheus, Grafana, ELK stack, etc.) to proactively detect issues and maintain system uptime for both standard applications and AI frameworks.
• Security & Compliance: Implement DevSecOps best practices including vulnerability scanning, policy enforcement, and secure secrets management, ensuring regulatory compliance where needed.
• Team Leadership & Mentorship: Lead, mentor, and grow a team of DevOps and MLOps engineers, promoting a culture of continuous learning, collaboration, and high performance.
  
  

• 8+ years of experience in DevOps or related roles, with at least 2 years in a senior/lead capacity.
• Proven experience designing and operating production infrastructure in cloud environments (AWS, Azure, or GCP).
• Hands-on expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes).
• Solid background in scripting and coding (Shell, Python, Go, or similar languages).
• Experience building and managing CI/CD pipelines with tools like Jenkins, GitLab, or GitHub Actions.
• Practical knowledge of AI/ML workflows, including data pipelines, model training, and model deployment (MLflow, Kubeflow, or similar frameworks).
  
  

• 8-11 Years
  
  

• Primary Skill: DevOps Engineering
• Sub Skill(s): DevOps Engineering
• Additional Skill(s): AI/ML Architecture, DevOps Engineering