AI Systems Engineer (Codex Agents)

TL;DR

AI Systems Engineer (Codex Agents): Building the agent harness that turns model capability into real-world action with an accent on prompting, interpreting outputs, safe execution, and production reliability. Focus on designing execution loops, sandboxing, orchestration, evaluation frameworks, and observability systems to improve agent solve rate, latency, and cost.

Location: San Francisco

Salary: $230K – $385K + Offers Equity

Company

hirify.global is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

• Design and build the core agent harness and execution loop for interpreting model outputs, using tools, executing code, and completing long-horizon tasks safely.
• Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents in real development environments.
• Develop evaluation, experimentation, and debugging systems to distinguish issues across harness, model, inference/runtime, and product failures.
• Run ablations across prompts, interfaces, context, tool-use, and harness to improve solve rate, reliability, latency, and cost.
• Improve observability, profiling, and diagnostics across the agent stack, including backend, inference, GPUs, and fleet capacity.
• Collaborate with research to make the harness trainable and useful for frontier agentic models, building shared primitives for other teams.

Requirements

• Built or operated production systems in distributed systems, infrastructure, developer tooling, sandboxing, virtualization, cloud platforms, or ML systems.
• Hands-on across layers: Rust systems code, Python, APIs, agent orchestration, evals, inference, runtime constraints.
• Experience with LLM applications, coding agents, evals, model deployment, inference, or developer platforms.
• Strong focus on reliability, safety, performance, debuggability, and clean abstractions.
• Able to debug from evidence and fix ambiguous production failures quickly.
• Comfortable working close to research while shipping to production, with strong ownership and leadership in AI systems work.

Nice to have

• Deep Rust, systems, sandboxing, isolation, or low-level platform experience.
• Experience with coding agents, agent harnesses, tool-using LLMs, model evals, or post-training feedback.
• Background in compilers, kernels, runtimes, inference optimization, GPU systems, benchmarking, or performance engineering.
• Built production infrastructure used by many under high reliability and security constraints.
• Open-source infrastructure or developer-platform work with strong API taste.