Senior Site Reliability Engineer (SRE/DevOps)

As a Senior DevOps Engineer, you will work closely with Product, Engineering, and AI teams to shape our infrastructure strategy, design resilient cloud architectures, and ensure our platforms are secure, scalable, and high-performing. You will play a key role in bringing AI systems into production, enabling reliable delivery, strong observability, and operational excellence across our products and internal systems.

Your Responsibilities

• Design and operate secure, scalable, and high-quality infrastructure that supports modern applications and advanced AI workloads
• Build and maintain robust automation across CI/CD pipelines, infrastructure provisioning, and operational processes to improve reliability and minimize manual effort
• Integrate AI-driven solutions into operational workflows to enhance efficiency, detect anomalies, and accelerate delivery
• Apply strong systems engineering practices, including monitoring, incident management, performance optimization, and capacity planning
• Establish and uphold DevOps best practices, ensuring reproducibility, testing, documentation, and operational excellence
• Communicate technical decisions clearly and collaborate cross-functionally to support predictable delivery and effective problem-solving
• Provide mentorship and technical leadership, raising the level of platform engineering, DevOps maturity, and overall engineering quality across the organization

Requirements

• Experience & Discipline: 6+ years of progressive experience in DevOps, Site Reliability Engineering (SRE), Platform Engineering, or Infrastructure Engineering.
• Cloud Expertise: Strong, hands-on experience across multi-cloud environments (AWS, GCP, Azure), including expertise in networking, compute, storage, security, and cost optimization.
• Core Platform Stack: Deep expertise in containerization and orchestration and extensive experience with Infrastructure as Code (IaC) (e.g., Terraform, Pulumi, CloudFormation).
• AI/ML Infrastructure: Experience supporting or deploying AI/ML workloads (e.g., model inference, vector databases, GPU workloads), or strong familiarity with the infrastructure requirements for these systems.
• System Reliability: Proven ability to design, build, and operate highly reliable, scalable production systems utilizing advanced Zero-Downtime Deployment Patterns (e.g., Blue/Green, Canary, progressive delivery, Preview Environments).
• Modern Delivery & Tooling: Expertise in modernizing deployments via GitOps practices (e.g., ArgoCD, Flux) and building Self-Service Developer Platforms that enable engineering efficiency (e.g., environment automation, internal tooling).
• Networking & Edge Routing: Experience implementing and managing Multi-Cloud API Gateways and Edge Routing solutions.
• Security & Hardening: Strong background in platform security, including secrets management, Identity and Access Control (IAM), and Runtime/Security Hardening
• Observability: Solid understanding and practical experience with modern observability stacks.
• Mentorship & Communication: Excellent communication and collaboration skills with a proven ability to describe complex infrastructure decisions clearly and a background in mentoring engineers and driving improvements in engineering practices.
• Development Expertise: Familiarity with modern programming languages like Node.js, NestJS, and Python is highly desirable for extending DevOps capabilities or integrating tooling.