Applied AI Engineer Intern - Advancing Agent Quality

Brightstar.AI is an AI organization developing proprietary AI systems and a Think Tank focused on applied artificial intelligence. The Applied AI Engineer Intern will build agent evaluation environments, automated judges, diagnostic tools, and data pipelines for the AI Twin Board and other agentic systems while contributing frontier AI research perspectives.

Responsibilities:

• Design, build, and scale realistic agent environments and task suites that reflect how Brightstar’s agents are actually used — board-level deliberation, research synthesis, diligence workflows, and multi-step tool use
• Develop agentic LLM judge, calibrate them against human expert evaluation, and benchmark Brightstar agents against leading frontier models
• Build trajectory-analysis frameworks and diagnostic tooling that root-cause agent failure modes — passivity, hallucination, persona drift, brittle tool execution — and feed fixes back into agent prompts, harnesses, and architecture
• Enable agents to generate and iterate on their own verifiers (automated test cases, checklists, ground-truth sets) to support effective exploration and iterative problem-solving
• Harvest multi-turn interaction trajectories into high-quality datasets and reward signals that support fine-tuning and post-training of the models Brightstar relies on
• Contribute to the AI Twin Board build-out as the initial focus, and extend the same evaluation approach to other Brightstar AI initiatives as the roadmap grows
• Contribute frontier AI research perspectives to the Brightstar.AI Think Tank as part of weekly review sessions and select strategic discussions
• Review relevant research papers, conference findings, and publications from leading AI institutions and labs as inputs to the Think Tank knowledge base and to Brightstar’s evaluation methodology
• Help interpret academic and technical developments for a business and investment audience, including implications for industry transformation and applied AI opportunities