Staff Engineer — Enterprise AI Systems & Evaluation

Ambral (YC S25); San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Significant equity and ownership

Equinox membership

Free meals, coffee, and snacks

Health insurance

Unlimited PTO

Job summary

Ambral is hiring to build a replayable enterprise history engine and deploy it in real workflows. You will work closely with the CTO to design production systems, process real enterprise data, and improve agent performance through reinforcement learning and context engineering.

You should have experience delivering production-grade software, processing large datasets, and turning business goals into measurable development tasks. Strong systems thinking is essential.

Qualifications

• Experience building production-grade software or in a quant role.
• Ability to process large, messy datasets at scale.
• Strong intuition for systems, abstraction, and data structures.
• Capable of turning fuzzy business objectives into measurable tasks.
• Able to move between research questions and production implementations.

Responsibilities

• Build and own production systems for a replayable enterprise history engine.
• Collaborate with customers to transform real data into scalable model-improvement workflows.
• Design graders and environments to enable verifiable rewards.
• Explore objectives and design tasks to maximize performance while controlling costs.
• Develop observability so agent behavior is explainable and measurable.

Skills

Production-grade software

Systems design

Data processing at scale

Observability

Reproducibility

Research to production

Customer collaboration

Tools

Python

ML tooling

Job description

Ambral is hiring to build a replayable enterprise history engine and deploy it in real workflows. You will work closely with the CTO to design production systems, process real enterprise data, and improve agent performance through reinforcement learning and context engineering.

You should have experience delivering production-grade software, processing large datasets, and turning business goals into measurable development tasks. Strong systems thinking is essential.