Location: San Francisco, CA
Applied AI Intern
See all roles: Open Positions – Crownlands
About Crownlands
Crownlands is building a precision neurology discovery platform to understand root causes, subtypes, and progression of neurodegenerative and psychiatric disease. We generate large-scale human multi-omic data and build the computational systems that translate biology into clear, decision-grade outputs. We operate from first principles: assumptions are hypotheses, and everything is worth pressure-testing.
About the Role
Crownlands is seeking a summer intern to work on our multi-agent AI scientist framework used for drug discovery and evaluation. This is a hands-on internship on a fast-moving, production AI system where priorities evolve as the platform grows. You will improve core parts of our agentic pipeline—expanding agent capabilities while strengthening observability, maintenance, and evaluation. The work spans tooling, infrastructure, and internal frameworks rather than a single fixed project. This role is a good fit for someone who enjoys building, iterating, and improving real systems in an environment with high ownership and autonomy.
What You’ll Do
- Agent workflow engineering: Design and implement agent-based AI workflows for drug discovery and evaluation.
- Reliability and observability: Improve stability, tracing, and debuggability of multi-agent systems (tool calling, iteration control, validation, guardrails).
- Evaluation and benchmarking: Help define benchmarks, metrics, and failure modes for agent performance; build evaluation harnesses and regression tests.
- Provider-agnostic abstractions: Build and maintain abstractions across multiple LLM backends/providers.
- Systems integration: Integrate agents with internal data systems, APIs, SQL databases, and execution environments (AWS preferred).
- Protocol design: Collaborate on prompt, schema, and protocol design for robust agent interaction.
What We’re Looking For
Required / strongly preferred:
- Demonstration of excellence in a competitive area, e.g., at the national level - interpret this broadly, and please bold this in your email.
- Strong Python skills and experience building ML systems beyond notebooks (pipelines, services, orchestration).
- Familiarity with LLM tooling, agent frameworks, or workflow engines (e.g., LangGraph, LangChain, or comparable custom systems).
- Experience working with structured data, APIs, SQL databases, and/or distributed systems (AWS preferred).