Lead Engineer, AI Agent Systems
Tasks
- Build failure recovery and self healing
- Build multi layer memory stores
- Build skill execution and management engines
- Build task workspaces for dynamic context organization
- Contribute code to critical platform modules
- Define agent layer boundaries and collaboration
- Deliver end to end observability and diagnostics
- Design agent loop runtime
- Develop MCP hub infrastructure
- Develop automated evaluation systems and feedback loops
- Develop long history compression and evidence traceability
- Develop sandboxed environments
- Implement agent middleware pipelines
- Implement authorization and cost control
- Implement checkpointing interruption and resumption
- Implement context information management across stages
- Implement file processing and transfer pipelines
- Implement multi tenant isolation and security controls
- Implement retrieval and knowledge access capabilities
- Implement structured degradation for limits
- Lead agent infrastructure architecture
- Lead technical decomposition architecture decisions and code reviews
- Manage hierarchical context budgets
- Manage task decomposition dependencies and scheduling
- Normalize tool outputs
- Orchestrate planning and sub agent workflows
- Own context orchestration design and implementation
- Standardize inputs and dynamic capability representation
- Translate business use cases into reusable platform capabilities
Perks/Benefits
- N/A
Skills/Tech-stack
Agent Framework | Asynchronous programming | Authorization | Concurrency Control | Cost Optimization | Distributed Systems | Docker | Kubernetes | LLM | MCP | Observability | Python | Retrieval-Augmented Generation | Security | Streaming | Token budgeting
Education
N/A
Roles
Engineer | Lead | Lead Engineer | Software Engineer | Staff Engineer
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