Backend Software Engineer

About the role

ABOUT ARTOS:

At Artos, we build tools that help biopharma companies create and manage their R&D documentation in a fraction of the time. If you’re looking to join a team whose mission is to fundamentally change the way that drug development gets done, we’d love to talk to you.

About the Role:

We're growing fast, and we're looking for an engineer who thrives in a high-velocity environment and wants to do meaningful work. At Artos, you'll help accelerate development of a platform that supports companies — from innovative biotech startups to the world's largest pharmaceutical firms — in delivering life-saving treatments to patients faster than ever before.

As a core member of Artos's engineering team, you'll play a critical role in developing, scaling, and expanding the Artos platform to serve regulatory needs for pharma and life science companies around the globe.

Qualifications:

- BS/MS in Computer Science, Engineering, or related field (or equivalent experience)

- 3+ years in software development with a focus on AI/ML applications

- Hands-on experience with GenAI applications: prompt engineering, RAG, data pipelines, and eval frameworks

- Experience building APIs with modern Python frameworks (FastAPI, Django, etc.)

- Experience deploying and scaling containerized apps in cloud environments (AWS preferred)

- Experience building CI/CD pipelines for production backend systems

- Familiarity with secure coding practices, ideally from a regulated industry (fintech, life sciences)

- Pluses: IaC (Terraform/Pulumi), React, knowledge of life sciences regulatory requirements

Requirements:

- Design, build, and maintain scalable backend systems in production

- Build APIs and services using Python frameworks (FastAPI, Django, etc.)

- Work with containerized apps and cloud infrastructure (Docker, AWS, Terraform)

- Implement CI/CD pipelines and debug production systems

- Rapidly apply LLM techniques: prompt engineering, fine-tuning, RAG

- Stay current with generative AI best practices and apply them pragmatically

- Communicate technical decisions clearly to both technical and non-technical audiences

- Collaborate across teams (product, medical writers, customer success)

- Navigate ambiguous requirements and execute independently

- Debug across system layers: application logic, model behavior, APIs, infrastructure

Other Information:

Very comfortable working in a fast-paced and intense startup environment

Willing to work in-person in our office in Mission Bay 4-5 days/week

Likes matcha KitKats, believes every LLM prompt is just Schrödinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system