Remote: Staff Backend Engineer for AI Platform

GoDaddy Inc.; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote work options

Competitive pay

Generous time off

Parental and wellness leave

Healthcare

Job summary

GoDaddy is seeking a Staff Software Engineer to lead the design and evolution of the ML infrastructure, platforms, and services enabling ML models to run in production. You will collaborate with ML Scientists, Data Engineers, and Product teams across a globally distributed team.

This senior role emphasizes architecture influence, engineering excellence, and mentoring engineers while delivering robust, scalable ML-powered solutions.

Qualifications

• 7+ years of software engineering in distributed systems.
• Proficiency in Python, Go, and/or TypeScript with API design focus.
• CI/CD pipelines and cloud-native apps on AWS (ECS/EKS/Lambda).
• Experience with Docker, Kubernetes, and high-availability workloads.
• Leadership in technical initiatives and mentoring engineers.

Responsibilities

• Deploy and operate ML or generative AI workloads with frameworks (e.g., vLLM, Triton, TorchServe).
• Advance observability using OpenTelemetry, Prometheus, Grafana, CloudWatch.
• Work with vector databases, feature stores, caching (Valkey/Redis), and IaC (CDK, CloudFormation, Terraform).
• Manage GPU infrastructure, scheduling, performance tuning, and cloud cost optimization.
• Lead distributed teams and mentor engineers, leveraging AI-assisted dev tools.

Skills

Python

Go

TypeScript

API design

System architecture

Performance optimization

Tools

AWS

Docker

Kubernetes

ECS

EKS

CloudWatch

Job description

GoDaddy is seeking a Staff Software Engineer to lead the design and evolution of the ML infrastructure, platforms, and services enabling ML models to run in production. You will collaborate with ML Scientists, Data Engineers, and Product teams across a globally distributed team.

This senior role emphasizes architecture influence, engineering excellence, and mentoring engineers while delivering robust, scalable ML-powered solutions.