Engineering Manager, Agent Oversight

The shape of it

In the posting’s own words

Applied Intelligence Systems is Scale's team focused on pushing the frontier of what agentic applications can do. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale enterprises and governments demand. We're growing fast, with increasing traction across both commercial and public sector customers, and we're just getting started — this team will define what dependable, production-grade agentic AI looks like.

What it asks for · 6

• 7+ years of engineering experience, including 2+ years directly managing engineers or ML engineers responsible for a production ML/LLM-powered system — not just consuming a third-party ML API within a feature
• Hands-on familiarity with agent architectures — tool use, planning, multi-agent orchestration — and the technical depth to make informed tradeoffs with your team
• You can review ML experiment design or evaluation methodology well enough to ask sharp questions and earn credibility with ML engineers and scientists, even if you're not running the experiments yourself
• Track record owning the full lifecycle of platform-level infrastructure — from initial design through scaling it across multiple internal or external teams as usage, headcount, and complexity grow
• Experience collaborating with product managers, forward deployed engineering (FDE) teams, and customers to translate real-world requirements into prioritization decisions and shipped platform capabilities
• Track record of building and growing high-performing engineering teams — including hiring, retention, or measurable improvements in team output or velocity

Also a plus

• Experience building or overseeing evaluation, monitoring, or observability systems for ML/LLM-powered products in production
• Strong grasp of the full ML/agent development lifecycle — from experimentation through production deployment and iteration
• Deep understanding of modern LLMs and agentic system design, including prompt- and system-level optimization and integration with external tools, APIs, and services
• Published research, open-source contributions, or patents in agentic systems, LLMs, or applied ML
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints

Tools and skills named

Words the posting leans on

• agentic8×
• platform8×
• customers7×
• systems7×
• engineering6×
• agent5×
• design5×
• engineers5×
• evaluation5×
• production5×
• agentic applications4×
• building4×
• deployment4×
• enterprise4×
• government4×
• monitoring4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

More open at Scale AI

• AI Advisory ConsultantSan Francisco, CA; New York, NY
• AI Advisory PrincipalSan Francisco, CA; New York, NY
• AI Applications Ops Manager, GPSDoha, Qatar
• AI Builder InternSan Francisco, CA
• AI Infrastructure Engineer, Model Serving PlatformSan Francisco, CA; New York, NY
• AI Infrastructure Engineer, Sandbox PlatformLondon, UK