Sr Applied LLM Engineer

Sr. Applied LLM Engineer

• 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
  

Requirements

Life Science Tech: Benchling, Viva.

Legal/Compliance AI: Ironclad, Harvey.

Open Source Communities: LangChain, LangGraph, or Maestro contributors.