Backend Software Engineer
Artos AI · San Francisco Bay Area · 1 wk ago
HybridEngineeringFull-time
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 the 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 world.
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)
- Plus: 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