Staff AI/Agentic Engineer

What you'll do

• Lead the design and implementation of complex multi-agent systems including supervisor and planner/executor patterns.
• Establish standards for durable workflow design including state management, checkpoints, and idempotency.
• Drive context-engineering and retrieval strategies such as chunking, indexing, and memory hierarchies.
• Design evaluation systems to curate datasets and define task-success and safety metrics.
• Manage production reliability for high-risk systems by optimizing latency, cost, and incident response.
• Create reusable agent patterns, SDKs, and evaluation tooling for the platform paved road.
• Lead technical discovery with product managers and stakeholders to communicate feasibility and delivery commitments.
• Mentor mid-level and junior engineers and provide technical leadership on cross-team initiatives.

What we're looking for

• 7–10 years of software engineering experience with production distributed, API-driven, or workflow-intensive systems.
• Hands-on experience designing, coding, testing, deploying, and operating agentic or LLM-based applications in production at scale.
• Deep understanding of agent architecture, tool calling, durable state, multi-agent coordination, context engineering, retrieval, evaluation, observability, and safety controls.
• Strong software engineering ability in Python and at least one of TypeScript, Go, or Java, including distributed systems and secure SDLC.
• Experience defining measurable quality, safety, reliability, latency, and cost indicators to drive systemic improvement.
• Bachelor's degree in a related field or equivalent professional experience.
• Demonstrated ability to drive technical decisions autonomously and communicate effectively with technical leadership.
• Experience with agent frameworks (e.g., LangGraph, Temporal), regulated environments (GxP, HIPAA), or building secure tool-use systems (preferred).