AI agents are no longer demos. They're running in production: booking meetings, writing and shipping code, triaging support queues, orchestrating multi-step workflows. The companies building them need a different kind of software engineer: someone who understands LLM orchestration, tool use, evaluation frameworks, and what it actually takes to make an autonomous system reliable at scale.
We've been placing software engineers into agentic AI teams since before it had a name. We understand the stack, we know the candidates, and we can tell the difference between an engineer who has shipped production agents and one who has only read the papers.
Talk to us about agent hiringEngineers who build the orchestration layer: tool routing, memory systems, retry logic, and evaluation pipelines that make agents trustworthy in production.
Software engineers building LLM-powered products: RAG pipelines, fine-tuning workflows, prompt engineering at scale, and multi-model integrations.
Engineers who treat agent quality like a software problem, building automated test suites, benchmark harnesses, and monitoring that catches regressions before they reach users.
Software engineers building the next generation of developer tooling: AI-assisted coding, code generation, automated testing, and autonomous software development platforms.
We've placed engineers across agent infrastructure, AI applications, and DevTools. Tell us what you're building.
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