GoDaddyRemote

Staff Software Engineer - Backend

United States of America

Full Time

2 weeks ago

$182,000 - $273,000 USD

H1B Sponsor Likely

Key skills

PythonGoTypeScriptDistributed Systems and MicroservicesAPI Design and System ArchitectureAWS ECSAWS EKSAWS LambdaAWS DynamoDBAWS S3AWS IAMAWS CloudWatchDocker and KubernetesCI/CD PipelinesMachine Learning Workload Serving vLLMMachine Learning Workload Serving TritonMachine Learning Workload Serving TorchServeMachine Learning Workload Serving SageMaker EndpointsObservability OpenTelemetryObservability PrometheusObservability GrafanaObservability CloudWatchVector Databases and Feature StoresInfrastructure as Code CDKInfrastructure as Code CloudFormationInfrastructure as Code TerraformStakeholder CollaborationAIMachine LearningGenerative AIAWSTerraformKubernetesDockerECSEKSCloudFormationLambdaS3DynamoDBIAMCloudWatchSageMakerRedisPrometheusGrafanaOpenTelemetryCachingPerformance OptimizationCI/CDMentoring

About this role

GoDaddy is building AI and machine learning capabilities that power experiences for entrepreneurs worldwide. The Staff Software Engineer will lead the design and evolution of infrastructure, platforms, and services that enable machine learning models to run in production, while influencing architecture, driving engineering excellence, and mentoring engineers across a distributed team.

Responsibilities:

Experience deploying and operating machine learning or generative AI workloads using technologies such as vLLM, Triton, TorchServe, SageMaker Endpoints, or similar serving frameworks
Familiarity with modern observability practices and tools including OpenTelemetry, Prometheus, Grafana, and CloudWatch
Experience with vector databases, feature stores, caching technologies (Valkey/Redis), and infrastructure-as-code solutions such as CDK, CloudFormation, or Terraform
Knowledge of GPU infrastructure management, workload scheduling, performance tuning, and cloud cost optimization strategies
Experience serving as a technical lead or mentor for distributed engineering teams and leveraging AI-assisted development tools to accelerate software delivery

Requirements:

- Experience deploying and operating machine learning or generative AI workloads using technologies such as vLLM, Triton, TorchServe, SageMaker Endpoints, or similar serving frameworks
- Familiarity with modern observability practices and tools including OpenTelemetry, Prometheus, Grafana, and CloudWatch
- Experience with vector databases, feature stores, caching technologies (Valkey/Redis), and infrastructure-as-code solutions such as CDK, CloudFormation, or Terraform
- Knowledge of GPU infrastructure management, workload scheduling, performance tuning, and cloud cost optimization strategies
- Experience serving as a technical lead or mentor for distributed engineering teams and leveraging AI-assisted development tools to accelerate software delivery
- 7+ years of software engineering experience building and operating large-scale, production-grade distributed systems and microservices
- Strong proficiency in Python, Go, and/or TypeScript, with deep expertise in API design, system architecture, scalability, resiliency, and performance optimization
- Hands-on experience building CI/CD pipelines, cloud-native applications, and infrastructure on AWS using services such as ECS, EKS, Lambda, DynamoDB, S3, IAM, and CloudWatch
- Experience with containerization and orchestration technologies including Docker, Kubernetes, ECS, or similar platforms supporting high-availability production workloads
- Proven ability to lead complex technical initiatives, influence architecture, collaborate across diverse stakeholders, and mentor engineers in a fast-paced environment