Senior Software Engineer (AI/LLM or Backend Engineering)

Senior Software Engineer (AI/LLM or Backend Engineering)
San Francisco, CA
Permanent Full-time position

Qualifications:

• Bachelor s or Master s degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 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, Google Cloud Platform, 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