Backend Software Engineer

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 Schrodinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system