Applied AI Engineer

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 applicationsHands-on experience building LLM-based applicationsDesigning multi-step LLM workflows and task-specific agentsExperience working with frontier models (e.g., OpenAI, Anthropic, Google)Experience with AI tools as a user, specifically AI code editorsDeveloping advanced prompt engineering strategies, evaluation frameworks, and RAG pipelinesConducting technical R&D to explore and define the boundaries of model functionalityUse of evaluation tools such as Langfuse or LangSmithStrong backend engineering experience, including:Building APIs from the ground up using Python frameworks such as FastAPI and DjangoDeploying 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 applicationsAbility to create, orchestrate, and evaluate LLM-based agents and chained workflows with minimal oversightAbility to implement and orchestrate multi-step agentic workflowsAbility 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 functionalityAbility to stay current with emerging practices, models, and tooling in the generative AI ecosystem and apply them pragmaticallyAbility 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 spacesNice to Have:Worked with Infrastructure-as-Code tools such as Terraform or PulumiImplementing CI/CD pipelines (e.g., GitHub Actions)Experience working in or adjacent to regulated domains (life sciences, clinical R&D) is a plusFrontend development experience (e.g., React) is a plus, but not required Other Information:Very comfortable working in a fast-paced and intense startup environmentWilling to work in-person in our office in Mission Bay 4-5 days/weekLikes matcha KitKats, believes every LLM prompt is just Schrödinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system