TECHNOLOGY ARCHITECT/ Senior AI Engineer (Applied AI) - W2 Only

About the Role

This position focuses on designing and implementing advanced AI systems, including agentic workflows, memory architectures, and high-performance data retrieval infrastructure.

Responsibilities

• Agentic Workflows & Memory Systems
  • Build and debug production-grade, cyclic multi-agent workflows and state machines.
  • Implement multi-layered memory architectures, including short-term memory for active turn execution, long-term memory for cross-session state persistence, and episodic summarization to manage token context windows.
  • Design dependable function-calling patterns with automated retry logic and self-correction handlers.
• Data & Retrieval Infrastructure
  • Manage relational metadata schemas and execute optimized semantic vector similarity searches within a combined relational database layer.
  • Utilize document-store databases to persist unstructured execution payloads, dynamic agent states, and raw chat logs.
  • Develop hybrid RAG pipelines combining relational/exact-match queries with vector-space searches for high-precision retrieval.
• Production Reliability & Performance
  • Instrument end-to-end tracing to monitor agent execution steps, debug non-deterministic loops, and track token costs.
  • Create programmatic evaluation testing and scoring frameworks to benchmark agent accuracy before production deployment.
  • Write clean, concurrent, asynchronous Python code to handle high-throughput foundation model APIs.

Skills

• Stateful Orchestration
• Context & Memory Engineering
• Tool Call Management
• Vector & Relational Storage
• Document Persistence
• Hybrid RAG Pipelines
• Granular Tracing
• Automated Evals
• Core Backend Development (Python, DirectMemory)