# Senior/Staff/Principal Software Engineer - Python at ArteraAI

> Remote · United States · Principal · Software engineering · open. Source: https://alderhq.app/jobs/lever%3Aartera%3Acc5cbc4d-c7e7-4573-993f-526cb33f5a81 (read 2026-11-05).

## Facts (observed)

- Company: [ArteraAI](https://alderhq.app/companies/arteraai)
- Location text: Remote-US
- Where it can be done from (inferred): Remote · United States (evidence: "Remote role open worldwide")
- Posted: 2026-05-11 (178 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.lever.co/artera/cc5cbc4d-c7e7-4573-993f-526cb33f5a81
- Skills listed (inferred): Python, GraphQL, AWS, SQL

## Pay and sponsorship

- Posted pay: $180k–$240k per year (from the listing's pay field)
- Market band for similar posted roles (United States, n 467): p25 $206k, median $240k, p75 $282k

## Description (the employer's text)

About Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale.

As we scale, our core infrastructure must seamlessly handle complex workflows spanning billing platforms, electronic health record systems, and varied healthcare vendor networks. We are hiring a Software Engineer dedicated to building, optimizing, and automating Artera’s foundational data pipelines end-to-end—with an initial, heavy focus on agentic workflows.

### Essential Responsibilities:

Architect, deploy, and maintain secure, scalable agentic workflows within AWS to automate existing human-driven workflows.

Develop and launch Artera’s OCR tooling, with support from the AI team

Translate requirements from Sales, Finance, Customer Success, and Lab Operations into well‐scoped engineering deliverables with clear SLAs, observability, and rollback paths.

Develop Artera’s next generation of health system integration infrastructure (HL7, FHIR).

Use AI Code-gen and other AI‐assisted development tools to accelerate delivery, generating, reviewing, and refactoring Python code.

### Experience Requirements:

Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience.

5+ years of professional software engineering experience shipping and operating production systems.

Strong proficiency in Python

Demonstrated experience leading the design, development, and deployment of production-grade, highly available software systems in the cloud (AWS preferred).

Experience with version control (Git), CI/CD pipelines, automated testing

Strong written and verbal communication skills; able to work directly with Finance, Technical Product Management, and external vendor counterparts.

### Desired Experience:

Experience with AWS and ECS

Experience working with GraphQL and REST APIs

Experience with SQL and NoSQL databases

Experience with HL7, FIHR, and Electronic Health Record (ECR) integrations

### Here are few posts from our teammates, partners and customer voices to highlight the work we do:

- Artera Shapes the Future of Cancer Treatment Using Machine Learning on AWS
- How Artera AI test allowed Bruno to avoid hormone therapy
- Startups are using AI to predict responses to Cancer Drugs
- ArteraAI validates its Prognostic Model in Advanced Prostate Cancer
- How Artera Enhances Prostate Cancer Diagnostics Using AWS
Equal Employee Opportunity: At Artera, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients and physicians. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/lever%3Aartera%3Acc5cbc4d-c7e7-4573-993f-526cb33f5a81 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.