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:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)

2+ years of software development experience building and deploying AI/ML applications

Hands-on experience building LLM-based applications

Designing multi-step LLM workflows and task-specific agents

Experience working with frontier models (e.g., OpenAI, Anthropic, Google)

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

Use of evaluation tools such as Langfuse or LangSmith

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)

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 implement and orchestrate multi-step agentic workflows

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

Nice to Have:

Worked with Infrastructure-as-Code tools such as Terraform or Pulumi

Implementing CI/CD pipelines (e.g., GitHub Actions)

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

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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