DevOps Engineer

• Design, build, and maintain hybrid infrastructure across on-premises bare-metal systems and AWS
• Build and evolve Terraform and Terragrunt Infrastructure-as-Code
• Manage Puppet and Ansible configuration across environments
• Maintain and improve networking, including routing, load balancing, tunneling, and security features
• Build and maintain GitLab CI/CD pipelines for infrastructure and platform delivery
• Participate in incident response and postmortems
• Apply AI tools to reduce toil and improve automation, tooling, and incident response
• Collaborate with Product and engineering teams to translate business needs into infrastructure solutions
• Improve team processes and infrastructure practices

DevOps Engineer – Mid-Senior

• Specialize in Kubernetes and other CNCF technologies
• Work primarily in AWS, with opportunities to engage with other cloud platforms or physical servers
• Use GitOps in daily work and automate with Terraform and Ansible
• Develop and enhance CI/CD pipelines with GitLab, ArgoCD, and Helm
• Manage and optimize Percona, MySQL, and MongoDB databases
• Build logging and monitoring infrastructure with Prometheus, Grafana, Alertmanager, and Loki
• Collaborate closely with product engineering teams
• Maintain a stable, modern, scalable platform for applications seeking SOC2 certification

Senior DevOps Engineer

• Design, deploy, and maintain cloud and on-premises infrastructure for big data platforms and Generative AI workloads
• Build secure, scalable AWS or Azure environments, including multi-account/landing-zone setups, networking, IAM, and identity integration
• Deploy, scale, and operate production LLM-powered services, including agent frameworks, RAG pipelines, vector stores, and orchestration layers
• Ensure AI services are reliable, observable, and cost-efficient
• Use Terraform and Ansible for repeatable deployments
• Manage secrets, keys, and AI provider credentials securely using AWS Secrets Manager, Vault, and KMS
• Build and maintain CI/CD pipelines with GitLab CI and ArgoCD for infrastructure, data applications, and AI services
• Manage automated testing, static analysis, AI-assisted code review, and release processes
• Deploy and operate EKS/AKS Kubernetes clusters for big data and AI workloads
• Optimize GPU/CPU resource utilization for inference and batch jobs
• Implement and optimize observability using Prometheus, Zabbix, Grafana, and cloud-native tools
• Monitor LLM-specific signals including model latency, error rates, prompt/response quality, and cost
• Collaborate with network and security teams on secure connectivity, VPNs, Transit Gateway, and private endpoints
• Apply compliance best practices in regulated industries
• Identify and resolve performance bottlenecks across big data clusters and AI inference workloads
• Use AI tools such as Claude Code and MCP-based assistants for code review, IaC generation, runbook automation, incident response, and team adoption

Senior DevOps Engineer – Big Data, AI Platforms

• Design, maintain, and automate monitoring, alerting, and observability solutions using Datadog, Prometheus, and Grafana
• Define and monitor SLIs/SLOs, improve incident response processes, and support on-call operations
• Lead or support production incident resolution
• Conduct blameless post-mortems and drive continuous reliability improvements
• Optimise cloud infrastructure costs while maintaining performance, scalability, and reliability
• Support capacity planning, performance tuning, and resilience initiatives through monitoring and load-testing insights
• Collaborate with engineering, QA, security, and product teams
• Contribute to system design reviews focused on reliability, scalability, and operational excellence
• Share knowledge, mentor colleagues, and contribute to the Site Reliability Engineering Community of Practice

Senior SRE Engineer

• Design and build scalable, high-performing infrastructure using Infrastructure-as-Code practices
• Maintain and evolve on-premises infrastructure, solving complex challenges at massive scale with 60PB+ monthly data traffic
• Implement monitoring for infrastructure health and business metrics
• Own and defend architectural and technical decisions
• Drive continuous improvement of infrastructure, tooling, and practices
• Evaluate emerging technologies and build roadmaps for adopting them smoothly

• Design, implement, and maintain secure, scalable, and resilient AWS infrastructure using Infrastructure as Code and automation
• Manage and improve cloud networking, security, monitoring, backup, and disaster recovery capabilities
• Develop and maintain reusable Terraform and Terragrunt modules for consistent multi-environment deployments
• Administer and optimize Linux environments, particularly RHEL
• Operate and enhance monitoring, observability, and alerting solutions
• Create actionable dashboards and insights for proactive issue detection and resolution
• Support incident response, troubleshooting, root cause analysis, and post-incident reviews
• Collaborate with engineers, architects, and technology teams
• Champion DevOps best practices and improve platform reliability, performance, and operational excellence