About this 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