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Ema is building an Agentic AI platform to transform enterprise productivity by enabling organizations to delegate repetitive tasks to AI employees. Founded by former executives from Google, Coinbase, Flipkart, and Okta, the company is backed by top-tier investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. With offices in Silicon Valley, London, Bangalore, and Vancouver, Ema operates at the frontier of production-grade Agentic AI.
We seek an experienced DevOps Engineer to join our growing infrastructure team and play a pivotal role in designing and building our platform as we scale our product and user base. You will work in a dynamic, fast-paced environment ensuring reliability, scalability, and performance of our systems, with focus on service architecture, deployment, distributed systems, data and ML infrastructure, and security.
Key responsibilities include:
- Partner with product teams to architect and design foundational infrastructure for our products
- Design, develop, and deploy highly available, scalable multi-tenant SaaS solutions on AWS, Azure, or GCP using Kubernetes, Helm, Terraform, and Istio
- Drive automation of infrastructure tasks from provisioning to configuration management and deployment using Terraform, Ansible, and Kubernetes
- Collaborate with software development teams to refine CI/CD pipelines using GitHub Actions and Cloud Build, enhance service interfaces, and improve developer experience
- Perform scripting in Shell and Python
- Architect and implement advanced observability solutions using Prometheus, Grafana, Sentry, and PagerDuty
- Proactively identify and remediate infrastructure vulnerabilities
- Monitor system health, analyze performance metrics, and recommend enhancements including database query optimization
Required qualifications: Bachelor's or Master's degree in Computer Science or related field; 7+ years of infrastructure engineering experience, preferably with Azure; excellent problem-solving skills; ability to work independently and as part of a team; experience with global teams; experience with air-gapped or private cloud environments.
Nice-to-have skills include MLOps experience, advanced observability architecture, comprehensive testing frameworks (Selenium), sophisticated multi-cloud network designs, query optimization, and event-driven data/ML infrastructure experience.
