Lead Engineer, AI Agent Systems

• Lead the architecture and evolution of next-generation agent infrastructure designed for complex knowledge-intensive work.
• Define clear boundaries and collaboration mechanisms across three core layers: the execution engine context and reasoning orchestration and the agent capability foundation. Ensure high availability reliability and long-term extensibility in environments with a low tolerance for hallucinations and incorrect outputs.

Agent Execution Engine

• Design and implement the Agent Loop runtime and its middleware pipelines.
• Lead the execution and orchestration of planning and sub-agent workflows including task decomposition dependency management concurrency control and execution scheduling.
• Build mechanisms for checkpointing interruption and resumption failure recovery self-healing authorization and cost control to ensure the reliable execution of long-running and complex multi-step tasks.

Context and Reasoning Orchestration

• Own the design and implementation of core context orchestration capabilities.
• Develop strategies for input standardization dynamic capability representation and hierarchical context-budget management including structured degradation when resource or context limits are reached.
• Build structured task workspaces that support efficient organization of dynamic context. Address challenges including long-history compression tool-output normalization evidence traceability and the management of information across different stages of a task.

Agent Capability Foundation

Lead the development of foundational agent capabilities including:

• Secure sandboxed environments using technologies such as Docker Kubernetes and AST-based controls
• Multi-layer memory stores
• Retrieval and knowledge-access capabilities
• An MCP (Model Context Protocol) Hub
• Skill execution and management engines
• File-processing and transfer pipelines
• Multi-tenant isolation and security controls
• End-to-end observability and diagnostics

Technical Leadership and Team Enablement

• Remain hands-on and personally contribute code to critical platform modules.
• Lead technical decomposition architecture decisions code reviews and the development of automated evaluation systems and feedback loops.
• Guide the engineering team in translating specific business use cases into reusable platform and infrastructure capabilities.