Applied AI Engineer - Agent Systems & Orchestration

Day One Partners; New York (NY); On-site; USD 120,000 - 210,000; Full time

Job summary

Day One Partners is partnering with an early-stage AI startup to hire 1–2 Applied AI Engineers. You will own the intelligence and infrastructure behind production agents, focusing on memory, orchestration, and system reliability.

You’ll work on frontier models, develop Evals and benchmarks, and build scalable sandboxed agent infrastructure, taking ownership from experimentation through deployment.

Qualifications

• Demonstrated experience building agent systems, harnesses, evals, benchmarks, or related AI infrastructure.
• Strong software fundamentals with depth in backend or distributed systems.
• Ability to reason about agent performance, design experiments, and diagnose failures.
• Experience addressing scalability, security, reliability, and isolation in production workloads.
• High technical ownership and comfort solving problems without established best practices.

Responsibilities

• Design and improve agent memory, context management, task execution, and multi-step orchestration.
• Build and optimize agent harnesses, including tool use, prompting, planning, feedback loops, and failure recovery.
• Develop evals and benchmarks that measure agent quality, regressions, and improvements.
• Build infrastructure for running and scaling sandboxed agents with isolation, observability, reliability, and cost/performance.
• Own difficult technical problems end-to-end from experimentation to production deployment.

Skills

Agent systems

Backend engineering

Distributed systems

Production AI systems

Security and reliability

Job description

Day One Partners is partnering with an early-stage AI startup to hire 1–2 Applied AI Engineers. You will own the intelligence and infrastructure behind production agents, focusing on memory, orchestration, and system reliability.

You’ll work on frontier models, develop Evals and benchmarks, and build scalable sandboxed agent infrastructure, taking ownership from experimentation through deployment.