Responsibilities :

- Own the reliability, scalability, and performance of production systems and services.

- Design and implement highly available, fault-tolerant, and distributed infrastructure.

- Define and drive observability strategy, including monitoring, logging, and alerting.

- Build and maintain scalable CI/CD pipelines to enable fast and reliable deployments.

- Automate infrastructure provisioning and operational workflows using IaC tools.

- Lead incident management, root cause analysis (RCA), and implement preventive measures.

- Define and track SLIs, SLOs, and SLAs aligned with business and product requirements.

- Collaborate closely with engineering teams to improve system design, deployment processes, and operational excellence.

- Optimize cloud infrastructure for cost, performance, and efficiency.

- Own and improve on-call processes; mentor engineers in handling production incidents.

- Drive best practices for security, networking, and infrastructure reliability.

- Participate in architecture and design reviews to ensure system resilience and scalability.

- Document system architecture, runbooks, and operational processes.

Requirements :

- 8+ years of experience in DevOps, SRE, or Cloud Engineering roles.

- Strong scripting skills in Bash and Python for automation; experience building internal tooling or services in Python with solid software engineering fundamentals is a strong plus.

- Hands-on experience with cloud platforms such as AWS, GCP, or Azure.

- Expertise in Infrastructure as Code tools like Terraform, Ansible, or CloudFormation.

- Strong experience with containerization (Docker) and orchestration (Kubernetes).

- Solid understanding of Linux systems, networking concepts, and security best practices (IAM, VPNs, firewalls).

- Experience with monitoring and observability tools like Prometheus, Grafana, ELK Stack, New Relic, or Datadog.

- Proven experience in building and maintaining CI/CD pipelines (Circle CI, ArgoCD, Jenkins, GitHub Actions, GitLab CI, etc.).

- Deep hands-on experience owning cloud security end-to-end.

- Strong debugging and troubleshooting skills for complex production systems.

- Comfortable operating in fast-moving engineering environments, balancing long-term infrastructure investment with immediate operational needs.

- Experience owning and continuously improving on-call processes - including rotation design, escalation policies, runbook culture, and post-incident review cadence.

Nice to Have :

- Experience with large-scale distributed systems and microservices architecture.

- Exposure to service mesh technologies and advanced Kubernetes ecosystems.

- Hands-on experience with cost optimization and capacity planning in cloud environments.

- Familiarity with chaos engineering and reliability testing practices.

- Experience mentoring engineers and driving engineering best practices.

- Prior involvement in architectural reviews and cross-team technical decision-making.

- Strong understanding of compliance, security standards, and DevSecOps practices.

- Experience building internal developer platforms or self-service infrastructure tools.

- Development exposure - experience contributing to backend services or application code (e.g., APIs, microservices), with strong software engineering fundamentals.

- MLOps experience - familiarity with deploying, monitoring, and managing ML models in production, including tools like ML pipelines, model versioning, and data workflows