# Software Engineer

**Company:** [Artera](https://hotfix.jobs/companies/artera)
**Location:** Remote
**Role:** DevOps / SRE
**Salary:** $140k – $180k/yr
**Experience:** 5+ years
**Skills:** Python, AWS, Kubernetes, EKS, ECS, AWS Lambda, EC2, Terraform, Aws Cdk, S3, Efs, Fsx, CI/CD, Grafana, Prometheus
**Posted:** 2025-06-04

> Build and maintain scalable compute infrastructure (AWS Kubernetes, ECS, Lambda) powering AI/ML products for cancer diagnostics. Optimize ML training/inference workflows, infrastructure-as-code, and platform tools for developer productivity, security, and cost efficiency. Requires 3+ years Python and infrastructure experience.

## Job Description

## Responsibilities
- Design, build, and maintain compute infrastructure programmatically (AWS Kubernetes/EKS, AWS ECS, Lambda, and EC2) that powers Artera's AI products at scale.
- Work closely with stakeholders to define and refine the platform's architecture, ensuring scalability, observability, reliability, and performance.
- Build out core infrastructure, tooling, and software development processes.
- Work closely with machine learning engineers to optimize training and inference workflows with efficiency and cost in mind.
- Contribute to a range of platform engineering projects, from one-off solutions to long-term systems.
- Contribute to cloud infrastructure security tools and services.

## Requirements
- 2+ years managing containerized infrastructure at scale with a strong security mindset.
- 3+ years building services and tools using Python with a software engineering mindset.
- 2+ years building infrastructure automation solutions using Infrastructure-as-Code (e.g., Terraform, AWS CDK).
- Experience with AWS storage services: S3, EFS, FSx.
- Experience with CI/CD pipelines.
- Demonstrated integrity and consideration for appropriate data governance when working with sensitive, confidential data.

## Nice-to-Haves
- Experience with infrastructure observability and monitoring tools (e.g., Grafana, Prometheus, Datadog).
- Experience supporting ML/AI workloads — GPU instance management, training cluster optimization, batch inference pipelines.
- Familiarity with cost optimization strategies for cloud compute at scale.
- Experience with secrets management and cloud security tooling (e.g., AWS IAM, Vault, KMS).
- Contributions to internal developer tooling or platform libraries consumed by cross-functional teams.

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**Apply:** https://hotfix.jobs/jobs/b894b754-b8d6-4b2e-9ecb-0790a92f9b4d
**Canonical:** https://hotfix.jobs/jobs/b894b754-b8d6-4b2e-9ecb-0790a92f9b4d