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HUD

Live runtime data for AI coding

Senior Software Engineer - Infrastructure

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Have owned production cloud infrastructure for a high-availability, user-facing platform, with responsibility for uptime, performance, deployment safety, and cost.
  • Have deep experience with AWS infrastructure and containerized systems; experience with tools like Terraform, Kubernetes/EKS, Docker, EC2, CodeBuild, ECR, S3, IAM, load balancers, networking, and secrets management is strongly preferred.
  • Have built or operated CI/CD, environment management, release automation, observability, alerting, and incident response systems.
  • Have strong backend engineering judgment and be able to reason about service architecture, APIs, databases, asynchronous systems, queues, scaling limits, and production failure modes.
  • Be able to write clean, maintainable code and apply strong software engineering judgment across product architecture, infrastructure, backend systems, and developer workflows.

Responsibilities

  • Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services.
  • Build and maintain AWS infrastructure with Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management.
  • Design and improve backend and platform systems for scale, including capacity planning, autoscaling, queueing, backpressure, cleanup jobs, retries, and rollback paths.
  • Define and improve dashboards, alerts, logs, traces, service-level objectives, runbooks, and on-call workflows so failures are detected, debugged, and resolved quickly.
  • Build reliable CI/CD, release automation, environment management, and deployment workflows that improve developer productivity and reduce production risk.
  • Write clean, maintainable code where needed to automate systems, improve backend services, and create internal tooling.

Desired Qualifications

  • Experience operating infrastructure for data-heavy, machine-learning/artificial-intelligence, workflow, marketplace, developer-tools, or enterprise platforms.
  • Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services.
  • Experience reducing cloud spend through better architecture, autoscaling, workload placement, caching, cleanup systems, or observability.
  • Experience building internal platforms or tools that make engineers faster without hiding too much complexity.

About the Company

HUD

Live runtime data for AI coding

HUD builds a Runtime Code Sensor that links live production software with AI-powered coding assistants. Developers add a lightweight SDK to their apps to stream real-time information about how code behaves—such as errors, latency, performance, and how functions are used—directly to AI tools like GitHub Copilot and other code generators. The product works by feeding ongoing, context-rich data from a running system into AI models so generated code can be aware of real-world conditions rather than just static code. This makes AI-generated code safer and more reliable in production. HUD differentiates itself by enabling production-aware development, providing continuous feedback from live environments rather than relying on static analysis or old logs. The company’s goal is to help software teams build higher-quality software faster with fewer bugs and better performance by bridging the gap between AI-generated code and real-world usage.

Company size
51-200
Company stage
Early VC
Total funding
$21.2M
Headquarters
San Francisco, CA
Founded
2025

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