Staff Software Engineer, Agentic AI Systems (AI)

TL;DR

Staff Software Engineer, Agentic AI Systems (AI): Leading the evolution of the hirify.global AI Assistant platform, focusing on agent orchestration, sandboxed file systems, code execution, and latency optimization. Focus on pushing the envelope of value provided to customers, creating delightful user experiences and enhancing our products using the latest advances in machine learning, LLMs, and AI agents.

Location: San Francisco, CA

Company

hirify.global is the Agentic AI Assistant platform that empowers the entire workforce.

What you will do

• Lead and take on exciting and difficult engineering challenges to build and evolve capable AI agent systems that are reliable.
• Define, drive, and deliver frontier AI distributed systems and ensure they are productionized at scale.
• Set technical direction, influence roadmap, and drive the evolution of engineering areas of broad scope and impact.
• Set a high bar for writing robust, extensible, readable, and performant code, and raise the engineering standard for the team.
• Partner with senior subject matter experts across the company to align teams and build the best enterprise AI products the world has ever seen.
• Mentor and develop engineers on the team, including coaching on technical design, execution, and engineering excellence.

Requirements

• 6+ years experience designing, building, and improving production systems, ideally at scale.
• Demonstrated ability to lead technical design and execution across multiple projects and stakeholders.
• Ability to think and communicate clearly about complex engineering problems and systems, and to drive alignment across teams.
• Comfort giving and receiving feedback, and in holding yourself and your coworkers accountable to a high standard of operational excellence.
• Readiness to hit the ground running in a Mac development environment, programming in Python, Golang, and/or Java.
• Strong attention to detail and a track record of shipping high-quality, production-grade systems.

Nice to have

• Experience building with LLMs, particularly in iterating on prompts, on model selection, on cognitive architecture design, and on latency/correctness tradeoffs in a data-driven way.
• Hands-on experience driving one or more stages of a machine learning problem-solving lifecycle.
• Experience in AI fairness, privacy, permission controls, safety, and/or security.
• Experience designing and operating large-scale, high-reliability systems with strong observability, SLOs, and on-call excellence.

Culture & Benefits

• Our compensation package includes a market competitive salary, equity for all full time roles, exceptional benefits, and, for applicable roles, commissions or bonus plans.