$ cat jobs/agent-infrastructure-engineer-core-harness-superagent-imagineart-55428a4356d7.json
Agent Infrastructure Engineer — Core Harness (Superagent)
About ImagineArt We're redefining how the world creates and designs. ImagineArt is one of the fastest-growing GenAI companies in the world. We've scaled faster than most funded startups — with zero outside funding. $35M+ ARR crossed this year 100M+ social impressions Built and shipped our own image generation model, now ranked #3 globally for photo realism No funding. No shortcuts. Just a sharp, driven team building one of the strongest GenAI products in the world — and we're just getting started. We're looking for an Agent Infrastructure Engineer to own Superagent , our core agent harness that powers conversations, tool calls, and multi-step agentic workflows across our AI products. This is a deep systems and infrastructure role — not prompt engineering and not simply wrapping model APIs. You'll work on the core orchestration loop, tool-calling infrastructure, context and memory management, streaming, retries, evaluation, observability, and performance. Key Responsibilities Own the architecture, development, and evolution of Superagent , our core agent harness. Design and optimize the agent execution loop for latency, reliability, token efficiency, cost, and task completion. Build and improve core harness systems including context management, memory/state handling, tool routing, function schemas, structured outputs, retries, and error recovery . Build and maintain agent evaluation infrastructure to measure quality and guide engineering decisions with data. Integrate and benchmark multiple LLM providers and models , evaluating performance, cost, reliability, and capabilities. Implement performance optimizations such as caching, batching, parallel tool execution, and prompt/context compression . Build deep observability and instrumentation across agent runs, including tracing, logging, metrics, and regression detection. Extend and customize underlying agent frameworks when existing abstractions are insufficient. Build reliable integrations with evolving AI and tool e
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