Senior DevOps Engineer
Dynamo AI
IndiaremotePosted 14 days ago
Skill Required
DevOps-EngineerSite-Reliability-EngineerPlatform-EngineerCloud-Infrastructure-EngineerSenior-DevOpsSenior-DevOps-DeveloperSenior-Staff-DevOps-EngineerSenior-TechOps-EngineerSenior-DevOps-Platform-EngineerSenior-AWS-DevOps-EngineerSenior-DevOps-ArchitectDevOps EngineerDevOpsSystem DesignVaultGitHub ActionsCloud SecuritytroubleshootingObservabilityEngineeringPostgreSQLKubernetesPrometheusISO 27001networkingautomationTerraformdesigningsecurityMongoDBJenkinsPythonArgoCDdesignGitKafkaRedisFulltime
Key highlights
- 5+ years of strong hands-on experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure
Role overview
Dynamo AI is looking for a Senior DevOps Engineer to help build, scale, and operate the infrastructure powering our AI platform. This is a hands-on, high-ownership role for someone who can work independently, solve complex infrastructure problems, and thrive in a fast-paced startup environment.
Responsibilities
- Design, build, and operate highly available production infrastructure on AWS, with strong expertise in EKS, EC2, VPC, S3, RDS/Aurora, IAM, ECR, ElastiCache, Load Balancers, and other core AWS services.
- Build and improve CI/CD and release automation using Jenkins, GitHub Actions, Helm, ArgoCD, and GitOps.
- Manage infrastructure using Terraform and Infrastructure as Code principles.
- Build and operate Kubernetes platforms at production scale, including cluster management, upgrades, autoscaling, networking, security, and troubleshooting.
- Run and operate AI/ML workloads in production, with a strong understanding of the infrastructure challenges associated with AI systems.
- Deploy, scale, monitor, and optimize AI inference and model-serving workloads across Kubernetes and cloud infrastructure.
- Work with GPU-based workloads, including GPU scheduling, utilization, autoscaling, capacity planning, and optimization.
- Drive infrastructure efficiency by balancing performance, reliability, scalability, and cost across AI workloads.
- Own monitoring, logging, and observability using tools such as Prometheus, Grafana, Thanos, and OpenTelemetry.
- Implement secure secrets management using technologies such as HashiCorp Vault and External Secrets Operator.
- Develop automation and internal tooling using Python and Bash.
- Drive improvements around reliability, security, scalability, performance, and infrastructure cost.
- Participate in production incidents, root-cause analysis, and drive long-term fixes rather than short-term workarounds.
- Work closely with Engineering, ML/AI, Security, and Product teams to solve infrastructure and platform challenges.
Requirements
- 5+ years of strong hands-on experience in DevOps, SRE, Platform Engineering, or Cloud Infrastructure.
- Strong production experience with AWS and Kubernetes/EKS.
- Proven experience running AI/ML workloads or GPU-based workloads in production is highly valuable.
- Strong understanding of CI/CD, Infrastructure as Code, GitOps, observability, and cloud security.
- Excellent scripting and automation skills in Python and Bash.
- Experience operating production systems and troubleshooting complex infrastructure issues independently.
- Strong understanding of scaling, performance optimization, resource utilization, and cost management, particularly for compute-intensive workloads.
- Strong ownership mindset with the ability to take a problem from design to production.
- Experience working in a startup or fast-moving engineering environment is highly valued.
- Strong communication skills and the ability to work effectively across teams.
Nice to have
- Experience with AI inference platforms, model serving, LLM infrastructure, or ML platforms.
- Experience with GPU infrastructure such as NVIDIA GPUs and Kubernetes GPU scheduling.
- Experience with multi-region or highly distributed systems.
- Experience with SOC 2, ISO 27001, or other security/compliance requirements.
- Experience with PostgreSQL, MongoDB, Redis, Kafka, or similar distributed systems.
Additional details
- About Dynamo AI: Dynamo AI helps enterprises deploy AI systems that are reliable, secure, and production-ready. Our market-leading technical controls span AI evaluations, guardrails, agentic risk management, and observability. Backed by world-class talent, we partner with innovative, highly-regulated global organizations — across financial services, government, and beyond — to deploy meaningful AI use cases at scale, securely and compliantly.
- The Kind of Engineer We Want: We're looking for someone who builds, automates, and takes ownership — not someone who simply operates existing infrastructure.
- You should be comfortable with ambiguity, willing to dive deep into production problems, and constantly looking for ways to make our platform more reliable, secure, scalable, and cost-efficient.
- Most importantly, you should understand that AI infrastructure has a different set of operational challenges. We want someone who can help us run AI systems efficiently at scale — making the right trade-offs between GPU utilization, performance, reliability, scalability, and cost.
- This is a high-ownership role for someone who wants to make a meaningful impact on the infrastructure behind an AI platform as we scale.
- Originally posted on Himalayas