Applied LLM Engineer

Qualifications

• Bachelors or Masters 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 Schrodingers cat waiting to be observed and knows too many random facts about the Mongol postal system
  

Requirements