AI Agent Engineer

Architect and implement robust agentic frameworks supporting tool use, context retrieval, memory, and planning. Build modular agents for investigative tasks, scale LLM infrastructure, and develop prompt engineering, RAG, model serving, evaluation, observability, and safety capabilities.

Responsibilities

• Architect and implement agentic frameworks supporting tool use, context retrieval, memory, and planning
• Build modular agents that automate investigative tasks and augment analyst decision-making
• Extend and scale LLM infrastructure, including prompt engineering, RAG, and evaluation loops
• Design safe, observable, and auditable agent behaviors
• Evaluate reasoning, latency, success rate, and hallucination metrics and iterate using feedback and telemetry
• Contribute to rapid experimentation and ethical AI deployment

Requirements

• Strong engineering background with deep backend or systems experience, preferably in Python
• Hands-on experience with LLMs, agents, LangChain, semantic caches, and vector databases
• Experience working with agentic pipelines and optimizing information flow into AI systems
• Thoughtful system design focused on safety, scalability, and explainability
• High product empathy and a bias toward experimentation and iteration
• Knowledge graphs, task orchestration, or AI safety experience is a plus

Benefits

• Equity plan eligibility