Founding AI Systems Engineer

Ambral (YC S25); United States; On-site; USD 150,000 - 225,000; Full time

Benefits offered by this job

Equity

Equinox membership

Free meals

Health insurance

Unlimited PTO

Job summary

Ambral is hiring engineers to build a replayable environment engine anchored in real enterprise history. You will reconstruct a company’s context from past data and expose it through the same tooling used by production agents, enabling policy testing and measurement against real outcomes.

You will own production systems, work directly with the CTO and customers, and help design scalable data pipelines, evaluators, and model-improvement workflows while balancing performance and cost.

Qualifications

• 2+ years of experience building production software or in a quant role.
• Ability to process large, messy datasets at scale.
• Able to translate fuzzy business objectives into measurable tasks and signals.

Responsibilities

• Build the replayable environment engine over real enterprise history.
• Collaborate with customers to turn real enterprise data into scalable model-improvement systems.
• Develop the environment factory that converts data and task definitions into runnable environments.
• Design graders to turn business objectives into verifiable rewards.
• Mine useful tasks, trajectories, and evaluation cases from historical workflows.
• Experiment with learning objectives and task design.
• Create eval sets that are representative, reproducible, and resistant to overfitting.
• Balance model performance with inference cost across models, tools, contexts, and policies.
• Build replay and observability systems to make agent behavior explainable and measurable.

Skills

Production software

ML systems experience

Data processing at scale

Observability

Job description

Ambral is hiring engineers to build a replayable environment engine anchored in real enterprise history. You will reconstruct a company’s context from past data and expose it through the same tooling used by production agents, enabling policy testing and measurement against real outcomes.

You will own production systems, work directly with the CTO and customers, and help design scalable data pipelines, evaluators, and model-improvement workflows while balancing performance and cost.