Artos Verified
Manufacturing, Industrial Machinery
Backend Software Engineer
San Francisco, California, United StatesOnsiteFull TimePosted 2 months agoHidden Gem · YC Startup
Role summary
Artos is seeking a highly talented Backend Software Engineer with a startup mindset to join their fast-growing team. The role involves developing and scaling the Artos platform, which helps biopharma companies manage R&D documentation. Key responsibilities include building AI/ML and GenAI applications, designing and implementing scalable backend systems, developing APIs using Python frameworks, deploying containerized applications, and implementing CI/CD pipelines. Experience with cloud infrastructure, secure coding practices, and a willingness to learn about life sciences regulatory requirements are essential. The position is hybrid, requiring 4-5 days in the Mission Bay office.
### **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.
We’re growing _very_ fast right now, and we at Artos are looking for a hyper-talented, startup-minded engineer who can help us accelerate the development of a product that supports companies from innovative biotech startups to some of the largest pharmaceutical companies in the world in their mission to deliver life-saving treatments to patients faster than ever before.
As a core member of Artos’s engineering team, you will play a critical role in developing, scaling, and expanding the Artos platform to help serve regulatory needs for pharma and life science companies around the globe.
### **Qualifications**
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Equivalent relevant work experience may be considered in place of a degree.
* 3+ experience in software development, with a strong background in building AI/ML applications.
* Backend Software Development Experience, including:
* Experience building GenAI applications, with extensive, hands-on experience with complex prompt engineering, GenAI-driven data pipelines, evaluation/benchmarking frameworks, and RAG.
* Experience building APIs from the ground up using modern Python frameworks (FastAPI, Django, etc).
* Experience in deploying and scaling containerized applications in enterprise customer cloud environments.
* Experience building CI/CD pipelines for production backend applications using any tools (GitHub Actions, CodePipeline, CircleCI, etc)
* Experience with Infrastructure-as-Code tools like Terraform or Pulumi is a plus
* Experience with the above via cloud services (e.g. AWS, Azure, GCP), especially AWS, is a plus.
* Experience with secure coding practices, ideally from a regulated industry (e.g. fintech, life sciences)
* Experience with frontend development in React is a plus.
* Knowledge of regulatory requirements in the life sciences industry is a plus. Willingness to learn is a necessity.
### **Requirements**
* Ability to design, build, and maintain scalable backend systems in a production environment
* Proficiency in building APIs and services using modern Python frameworks (e.g., FastAPI, Django)
* Ability to work with containerized applications and cloud infrastructure (e.g., Docker, AWS, Terraform)
* Experience implementing CI/CD pipelines and debugging systems in production
* Ability to rapidly learn and apply new techniques in LLM development, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG)
* Ability to stay current with emerging best practices in generative AI and apply them pragmatically to product needs
* Ability to communicate complex technical issues and design decisions clearly to both technical and non-technical audiences
* Ability to collaborate effectively across teams, including product managers, medical writers, and customer success
* Ability to reason through ambiguous requirements, propose technical solutions, and execute quickly without extensive oversight
* Strong debugging skills across multiple 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
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.
We’re growing _very_ fast right now, and we at Artos are looking for a hyper-talented, startup-minded engineer who can help us accelerate the development of a product that supports companies from innovative biotech startups to some of the largest pharmaceutical companies in the world in their mission to deliver life-saving treatments to patients faster than ever before.
As a core member of Artos’s engineering team, you will play a critical role in developing, scaling, and expanding the Artos platform to help serve regulatory needs for pharma and life science companies around the globe.
### **Qualifications**
* Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Equivalent relevant work experience may be considered in place of a degree.
* 3+ experience in software development, with a strong background in building AI/ML applications.
* Backend Software Development Experience, including:
* Experience building GenAI applications, with extensive, hands-on experience with complex prompt engineering, GenAI-driven data pipelines, evaluation/benchmarking frameworks, and RAG.
* Experience building APIs from the ground up using modern Python frameworks (FastAPI, Django, etc).
* Experience in deploying and scaling containerized applications in enterprise customer cloud environments.
* Experience building CI/CD pipelines for production backend applications using any tools (GitHub Actions, CodePipeline, CircleCI, etc)
* Experience with Infrastructure-as-Code tools like Terraform or Pulumi is a plus
* Experience with the above via cloud services (e.g. AWS, Azure, GCP), especially AWS, is a plus.
* Experience with secure coding practices, ideally from a regulated industry (e.g. fintech, life sciences)
* Experience with frontend development in React is a plus.
* Knowledge of regulatory requirements in the life sciences industry is a plus. Willingness to learn is a necessity.
### **Requirements**
* Ability to design, build, and maintain scalable backend systems in a production environment
* Proficiency in building APIs and services using modern Python frameworks (e.g., FastAPI, Django)
* Ability to work with containerized applications and cloud infrastructure (e.g., Docker, AWS, Terraform)
* Experience implementing CI/CD pipelines and debugging systems in production
* Ability to rapidly learn and apply new techniques in LLM development, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG)
* Ability to stay current with emerging best practices in generative AI and apply them pragmatically to product needs
* Ability to communicate complex technical issues and design decisions clearly to both technical and non-technical audiences
* Ability to collaborate effectively across teams, including product managers, medical writers, and customer success
* Ability to reason through ambiguous requirements, propose technical solutions, and execute quickly without extensive oversight
* Strong debugging skills across multiple 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
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