Senior Applied Scientist - AI Agent Systems

About the role

This role focuses on building reasoning and decision systems using planning algorithms, search methods, and optimization techniques, rather than chatbot or RAG-style application development.

What you'll do

• Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking
• Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search
• Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth
• Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies
• Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies

What you need

• 4–5 yrs of experience
• Machine learning
• Python
• Prompt engineering
• System design
• LLMs
• Any graduate