Architecture Leadership and Evolution
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.