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