Backend Software Engineer

ArtosAISan Francisco, CA
$166,500 - $231,000Onsite

About The Position

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.

Requirements

  • 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)

Nice To Haves

  • IaC (Terraform/Pulumi)
  • React
  • knowledge of life sciences regulatory requirements

Responsibilities

  • 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
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