AI Application Engineer

Proven experience designing and deploying agentic AI systems or complex orchestration flows Deep understanding of reasoning patterns (e.g., chain-of-thought, self-critique, reflection loops) Proficiency in Python and experience with agent frameworks (LangChain, PydanticAI, AutoGen, Semantic Kernel) Strong grasp of LLM integration patterns with tools, APIs, and knowledge bases Ability to translate client problem requirements into modular reasoning flows Excellent communication skills for cross-functional and client-facing collaboration

Architect agent frameworks capable of reasoning across multiple steps and data sources Collaborate directly with enterprise clients to understand reasoning needs, workflows, and tool integration requirements Design planning and decision-making loops that integrate retrieval, tool use, and external APIs Implement strategies for multi-hop reasoning, synthesis, and constraint-based problem-solving Ensure retrieval outputs are structured for optimal reasoning use Evaluate agent performance across reasoning benchmarks, accuracy metrics, and task completion rates Guide engineering teams on agent orchestration platforms and best practices Maintain playbooks and reusable reasoning templates for client-specific workflows