Job Description:

• Design, implement, and maintain end-to-end CI/CD pipelines for software applications and machine learning models
• Automate build, test, deployment, and rollback processes
• Build, optimize, and scale cloud-native infrastructure using Kubernetes and Docker
• Manage and provision specialized computing resources, including GPU clusters, for high-performance AI workloads and model inferencing
• Own high-availability design in production environments
• Implement disaster recovery strategies, self-healing mechanisms, capacity planning, and performance tuning
• Champion Infrastructure as Code practices using Terraform, Ansible, and Helm
• Architect and refine monitoring, logging, and alerting systems using Prometheus, Grafana, and ELK/EFK stack
• Build the Internal Developer Platform and golden paths enabling product, model, and data-science teams to deploy without opening a ticket
• Collaborate with R&D, Data Science, Security, and Business teams to streamline workflows and eliminate bottlenecks
• Establish and enforce system stability and security standards
• Manage release workflows, implement Zero Trust access controls, oversee secrets management, and ensure SOC2/ISO27001 compliance
• Lead troubleshooting, root-cause analysis, and preventative remediation during complex anomalies and major incidents
• Convert incident learnings into automation to prevent recurrence

Requirements:

• Bachelor's degree or above in Computer Science, Engineering, or a related technical field
• 5+ years of hands-on experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles
• Expert-level knowledge of Linux operating systems and core networking principles, including TCP/IP, DNS, HTTP, Load Balancing, and VPCs
• Deep mastery of Docker and Kubernetes orchestration, including cluster management and production-level best practices
• Proficiency designing and managing infrastructure on major public or hybrid cloud platforms, including AWS, GCP, Azure, or Alibaba Cloud
• Experience with multi-cloud and hybrid-cloud strategies
• Strong coding and scripting capabilities in at least one major language such as Go, Python, or Shell
• Systematic and practical understanding of CI/CD methodologies, Infrastructure as Code (IaC), observability paradigms, and SRE principles
• Exceptional problem-solving abilities and sharp technical judgment
• Excellent cross-team communication skills
• Preferred: Familiarity with MLOps practices, model serving/inferencing frameworks such as vLLM, TGI, or Triton Inference Server
• Preferred: Experience managing GPU clusters for AI/ML workloads
• Preferred: Experience with large-scale distributed systems or high-concurrency environments
• Preferred: Hands-on experience designing and building Internal Developer Platforms (IDP)
• Preferred: Familiarity with Zero Trust architecture, automated security testing (DevSecOps), SOC2, or ISO27001
• Preferred: Prior experience as a Technical Lead, mentoring junior engineers, or managing DevOps teams
• Preferred: Experience wiring an LLM-driven code/config helper into a pipeline or strong opinions on how to
• Must comply with applicable work authorization and equal employment requirements in the relevant country, state, and local jurisdictions

Benefits: