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# Sr. Platform Software Engineer

- **Company:** The Standard
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Continuous Integration, Software Debugging, Distributed Systems, Github, System Software, Datadog, Data Logging, Delivery Pipeline, Backend, Infrastructure Automation Frameworks, Machine Learning Operations, Dynatrace, Docker
- **Published:** July 12, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=00e7e05572f1f556

## About the Role

* Experience in high-growth or early-stage startups
 * Experience with AI/ML infrastructure
 * Experience designing multi-service distributed systems

## Description

We're looking for a Senior Platform Software Engineer to build the systems, tooling, and internal platform that make engineers dramatically more productive.

This role sits at the intersection of:

 * Platform engineering
 * Developer experience (DevEx)
 * Infrastructure automation
 * Distributed systems

You'll build the foundation that enables engineers to Ship faster, Deploy safely, Debug quickly & Operate confidently in production, * Build and evolve our internal developer platform (IDP)

 * Create self-service tooling that makes spinning up services, environments, and infrastructure effortless
 * Improve local development workflows, testing, deployment ergonomics, and developer feedback loops
 * Reduce operational friction through automation and platform abstractions

CI/CD & Release Engineering

 * Design and maintain scalable CI/CD systems using GitHub Actions &Infrastructure-as-code workflows
 * Improve: Build times, Deployment reliability & Rollback and recovery systems
 * Create deployment workflows that are fast, observable, and boring in production, * Design and operate cloud-native systems on AWS, EKS, Docker & Kubernetes
 * Improve platform scalability, resilience, and developer onboarding
 * Define service architecture and deployment standards across the engineering organization, * Own observability across the platform using Datadog, Metrics, Logging and Distributed tracing
 * Build dashboards, alerts, and operational tooling engineers actually use
 * Improve reliability, performance, and operational visibility across services, * Partner closely with backend and AI engineers to improve platform usability
 * Establish engineering standards and platform best practices
 * Make infrastructure feel like a product, not a support function


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