Member of Technical Staff (New Grad)

About the role

Ambral helps enterprises own the intelligence behind their most important workflows. We turn years of historical enterprise data—context, decisions, actions, and outcomes—into replayable environments and eval sets grounded in real workflows. These environments improve model performance through reinforcement learning, context engineering, harness design, and agent engineering, resulting in better, more cost-efficient AI powered by open-weight models that the company owns and controls.

We graduated from YC S2025, raised millions in funding, and are already deployed within multi-billion dollar enterprises. Now we're growing the founding team to build a replayable environment engine over real enterprise history.

Responsibilities

• Forward deploy with customers to understand their tasks and data
• Develop the environment factory that converts recorded enterprise data and task definitions into runnable environments
• Design graders to turn ambiguous business objectives into verifiable rewards
• Develop methods for mining 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
• Find the right combinations of models, tools, context, and policies to maximize performance while reducing inference cost
• Build replay and observability systems that make agent behavior explainable and measurable

You’ll have significant ownership over production systems, work directly with the CTO, and deploy into real enterprise workflows.

Requirements

• Experience building production-grade software (internships are ok) or in a quant role
• Strong software development skills and ability to build systems that process large, messy datasets at scale
• Great intuition about systems, abstraction, and data structures
• Comfort turning fuzzy business objectives into tasks and signals that can be evaluated reliably
• Ability to diagnose whether a model’s limitations come from the model itself, its context, its tools, its harness, or its training
• Ability to move between research questions and production implementation without treating them as separate jobs
• Care about reproducibility, observability, and understanding why a model behaves the way it does
• Looking to do the best work of your life and build something you’ll be proud of for decades

We care much more about what you’ve built and how you think than credentials or conventional career paths.

Benefits

• Significant equity and ownership
• Equinox membership
• Free meals, coffee, and snacks
• Health insurance
• Unlimited PTO

Pay

Compensation Range: $140K - $175K