- Job title
- Applied LLM Engineer
- Job location
- San Francisco, CA, US
- Job description
- ### **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 (or equivalent practical experience)
* 3+ years of software development experience, with a focus on building and deploying AI/ML applications
* Strong backend engineering experience, including:
* Building APIs from the ground up using Python frameworks such as **FastAPI** and **Django**
* Deploying and scaling containerized applications in cloud environments (e.g., **AWS**, **GCP**, **Azure**)
* Implementing CI/CD pipelines (e.g., **GitHub Actions**)
* Working with Infrastructure-as-Code tools such as **Terraform** or **Pulumi**
* Hands-on experience building **LLM-based applications**, including:
* Designing **multi-step LLM workflows** and task-specific agents
* Experience working with most frontier models (e.g. OpenAI, Anthropic, Google, etc…)
* Experience with AI tools as a user, specifically AI code editors
* Developing advanced **prompt engineering strategies**, evaluation frameworks, and RAG pipelines
* Conducting **technical R&D** to explore and define the boundaries of model functionality
* Familiarity with **secure coding practices**, ideally in regulated industries (e.g., life sciences, healthcare, fintech)
* Experience working in or adjacent to **regulated domains** (life sciences, clinical R&D) is a plus
* Frontend development experience (e.g., **React**) is a plus, but not required
### **Requirements**
* Ability to design and maintain scalable, production-grade backend systems for AI applications
* Ability to create, orchestrate, and evaluate **LLM-based agents** and **chained workflows** with minimal oversight
* Ability to debug and improve LLM-driven systems, identifying issues across multiple layers (model output, API behavior, system logic)
* Ability to conduct rapid experimentation and research on LLM capabilities and translate findings into production functionality
* Ability to **stay current with emerging practices, models, and tooling in the generative AI ecosystem** and apply them pragmatically
* Ability to communicate clearly with technical and non-technical collaborators (e.g., product managers, medical writers, customer teams)
* Ability to operate effectively in a fast-paced, ambiguity-heavy environment, managing shifting priorities and novel problem spaces
### **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
