BIO
AI Engineer
About this role
Join Bio Protocol's AI Agents team to design and scale intelligent agent systems that support decentralized biotech research. You'll build production-grade AI agents capable of planning, tool use, and reasoning while collaborating with scientists and engineers to create real-world impact in drug discovery and longevity research.
What you'll do
- Design and ship agent capabilities for planning, tool integration, memory management, and context handling
- Integrate agents with internal/external APIs, knowledge bases, and scientific datasets with robust safety measures
- Develop comprehensive testing, evaluation systems, and telemetry for agent performance monitoring
- Collaborate with scientists to analyze failure modes and iteratively improve agent reasoning
- Implement safety guardrails, sandboxed execution, and provenance tracking for scientific outputs
- Optimize system reliability through profiling, error handling, rate limiting, and observability instrumentation
What they're looking for
- Production Python and/or TypeScript development with strong systems design
- LLM application and agentic systems experience (tool use, RAG, structured outputs, evaluation)
- Agent frameworks (LangChain, LangGraph, AutoGen) and vector databases
- Cloud infrastructure (AWS, GCP, Azure), Kubernetes, Docker, CI/CD, and monitoring
- API design (FastAPI, gRPC, GraphQL) and system architecture
- Fine-tuning and reinforcement learning (preferred)
- Knowledge systems and ontology design (preferred)
- System safety and sandboxing practices (preferred)
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BIO
BIO builds a decentralized science platform that enables researchers and scientists to fund and commercialize biotech research through AI agents and blockchain coordination systems. The company is hiring Core Engineers, Full-Stack Engineers, AI/ML Engineers, Product Engineers, and QA Engineers to build foundational infrastructure, user-facing applications, intelligent agent systems, and quality assurance across its AI-driven research platform.
View all jobs at BIOLikely interview questions
- Walk us through a production LLM or agentic system you've shipped. How did you handle tool integration, failure modes, and evaluation?
- Describe your experience with agent frameworks like LangGraph or AutoGen. What were the trade-offs you encountered when building multi-step reasoning systems?