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# Software Engineer 1 - Cloud Infrastructure

- **Company:** Abnormal AI, Inc.
- **Location:** United States (Remote available)
- **Experience:** Starter
- **Salary:** $122,000.0 - $176,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Bash Shell, Cloud Computing, DevOps, Python (Programming Language), Runbook, Software Engineering, Software Systems, Claude Code, Technical Debt, AI Coding Agents, Kubernetes, Information Technology, Terraform, Software Version Control, Golang
- **Published:** October 17, 2026
- **Apply:** https://www.builtincolorado.com/job/software-engineer-1-cloud-infrastructure/11736088?handler=ApplyRedirect

## About the Role

* Bachelor's degree in Computer Science or a related technical field
 * 1-2 years of experience engineering cloud infrastructure solutions for microservice-based systems in production environments, accounting for optimal performance, reliability, security and cost.
 * 1+ years of experience with Python
 * 6 months - 1 year of experience with at least 2 of these areas: Terraform, AWS (or equivalent public cloud provider services), Kubernetes.
 * Experience working within mature software development practices, including source control, testing, and deployment.
 * Experience with on-call rotations, incident response, and operating production-grade systems
 * Experience using AI coding tools (e.g., Claude Code, Codex) in daily engineering work, with the judgment to validate, simplify, and reject AI-generated output that doesn't hold up in production.
 * Strong communication skills and the ability to thrive in a fast-paced, remote-first environment-balancing autonomy with collaboration, demonstrating a bias toward action, and maintaining a positive, constructive mindset.

Nice to Haves

 * Experience with Bash, Golang, and Terragrunt.
 * Prior experience building large-scale infrastructure-as-code abstractions.
 * AWS certifications., Field-based sales role responsible for expanding SOPHiA GENETICS' genomic solutions across Washington, Oregon, and Northern California. Develop new business, build relationships with oncologists, pathology teams, laboratories, and senior decision-makers, explain genomic testing value, address clinical and technical questions with subject-matter experts, and convert opportunities into bookings. Candidates need oncology or molecular diagnostics sales experience and knowledge of genomic biomarkers and treatment decision-making., Leads the design and development of software solutions, resolves complex technical problems, and provides guidance to engineering colleagues. Responsibilities include preparing technical documentation, reviewing code and testing, applying modern development methodologies, and supporting business initiatives. The role typically requires a bachelor's degree and at least three years of relevant experience. Preferred skills include Agile, cloud computing, DevOps, requirements analysis, system design, and project management.

## Description

The Platform & Infrastructure team is seeking a strong Cloud Infrastructure Engineer to help design, build, and operate the core compute and business-critical infrastructure services that form the foundation of Abnormal's product platform.
What you will do

 * Design, build, test, scale, monitor, and maintain secure, cost-efficient infrastructure in a multi-cloud environment (AWS and Azure)
 * Develop, evolve, and operate infrastructure as code to support repeatable, auditable, and scalable system provisioning.
 * Drive design collaboration by participating in technical discussions and providing constructive reviews
 * Contribute as a core member of an agile team with a strong sense of ownership and teamwork.
 * Partner closely with product and application engineering teams to understand platform needs and deliver well-designed, developer-friendly infrastructure abstractions.
 * Participate in an on-call rotation with a learning-oriented mindset, gaining insight into customer pain points, identifying systemic gaps, and driving long-term reliability improvements.
 * Drive down technical debt and operational toil by addressing root causes, automating repetitive work, and shaping roadmap investments to sustainably reduce both.
 * Use AI as a primary way to explore, design, and ship solutions, and automate repetitive work and operational toil. Improve team and system context (docs, runbooks, AI skills) so AI-assisted work gets better for everyone.