
Job Overview
Location
Remote
Job Type
Contract
Category
DevOps & SysAdmin
Date Posted
May 6, 2026
Full Job Description
đź“‹ Description
- • DevOps / Site Reliability Engineer role focused on owning and scaling cloud infrastructure to support AI data pipelines at BespokeLabs Inc.
- • Day-to-day responsibilities include managing AWS infrastructure (EC2, EKS, RDS, S3, IAM), Kubernetes clusters, CI/CD pipelines via GitHub Actions, monitoring stacks (Prometheus, Grafana, DataDog), and automating systems with Terraform or similar IaC tools
- • The team is small, fast-moving, and research-driven, working at the forefront of AI infrastructure with direct impact on frontier AI model training and evaluation
- • Opportunity to deepen expertise in cloud-native systems, improve reliability and performance of production environments, and contribute to high-impact AI research infrastructure
🎯 Requirements
- • 3–5 years of experience in DevOps, SRE, or infrastructure engineering
- • Strong AWS experience including EKS, EC2, RDS, S3, and IAM
- • Proficiency with Kubernetes for deployment, scaling, and troubleshooting in production
- • Experience building and maintaining CI/CD pipelines using GitHub Actions or similar tools
- • Hands-on experience with Infrastructure as Code using Terraform, Pulumi, or CDK
- • Proficiency in Python or Go for scripting and automation
🏖️ Benefits
- • Competitive compensation and meaningful equity
- • Flexible, remote-friendly work environment with low bureaucracy
- • Access to health, wellness, and learning & development benefits
- • Direct impact on frontier AI model training and evaluation infrastructure
- • Opportunity to work with a small, high-caliber team of AI research experts
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About BespokeLabs Inc.
BespokeLabs Inc. builds AI-driven software that personalizes digital experiences at scale. The platform ingests first-party user data to generate real-time content, messaging and product recommendations for e-commerce, media and SaaS companies, optimizing engagement and revenue without manual segmentation. Customers deploy lightweight JavaScript or server-side SDKs, configure goals and privacy controls, and receive continuously learning models that adapt to each visitor. Founded in 2019, the San Francisco–based company serves mid-market to enterprise clients across North America and Europe.
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