AI Researcher

About Traversal

Traversal is the AI Site Reliability Engineer (AI SRE) for the enterprise.

Production complexity was already outpacing what engineering teams could manage manually, and AI-generated code is accelerating that gap. Traversal is built for that challenge, autonomously understanding and reasoning across even the largest, most complex production environments to diagnose, fix, and prevent incidents. Our mission is to free engineers from endless firefighting and give them more time to focus on creative, high-impact work.

Today, Traversal operates in mission-critical environments at some of the world’s largest enterprises, including PepsiCo, Nubank, Harvey, and DigitalOcean. Our roots remain deeply embedded in AI research, and we’ve brought together researchers from institutions including MIT, Harvard, Berkeley, Columbia, and Cornell with world-class technical staff and operators from companies like Google, Meta, Datadog, ServiceNow, and Citadel Securities to take on one of the hardest problems for AI to solve. Traversal is backed by Sequoia Capital, Kleiner Perkins, Redpoint Ventures, and Khosla Ventures.

The Role

As an AI Researcher at Traversal, you'll work on improving the accuracy and speed of our agents — systems that autonomously diagnose and resolve production incidents for some of the world’s largest enterprises.

This is a hands-on, production-oriented research role. You will design experiments, run them on real data, and ship improvements. Not flag them — ship them.

You'll work end-to-end: identify a failure mode in agent reasoning, design an intervention, evaluate it against real customer traces, and get it into production. The tooling and infrastructure are in place. The research problem is hard. The feedback loop is fast. This is not a publish-papers role. It is a make-the-agent-work role – build-and-ship cutting edge AI.

Responsibilities

• LLM & Agent Research: Prototype and evaluate prompting strategies, reasoning workflows, and tool-use policies for agents operating on large-scale observability data and complex troubleshooting workflows. Ship improvements to production.

• Evaluation Design: Build and maintain eval harnesses that measure real accuracy improvements on actual customer incident types — not just benchmark scores. Own the loop from hypothesis to production measurement.

• Cross-Team Collaboration: Work closely with AI engineers, infrastructure teams, and product leads to bring research into production and close the loop between experimentation and impact.

• Stay on the Frontier: Track developments in LLMs, agent architectures, and AI alignment, translating insights into actionable improvements for Traversal’s domain.

• Training & Alignment: Apply fine-tuning, reinforcement learning, and reward modeling techniques to align AI behavior with real-world SRE workflows.

• Synthetic Data & Experimentation: Design pipelines to generate synthetic incidents and observability signals, enabling scalable training and testing in data-scarce environments.

Requirements

• PhD in Computer Science, Electrical Engineering, Statistics, or a related technical field; demonstrated depth in LLMs, agents, or applied machine learning

• Deep applied AI expertise, including strong working knowledge of LLMs, transformers, reinforcement learning, or neural networks in agentic systems

• Strong judgment in model evaluation and experimental iteration to improve product accuracy and behavior

• Strong software engineering depth, with the ability to work effectively in a complex production codebase and ship production-quality code

• Some experience shipping AI or ML systems to production

• Ability to run rigorous experiments, interpret results, and quickly translate learnings into product improvements

• Startup or early-team experience, with comfort operating in ambiguous environments and building without mature infrastructure

Nice to Have

• Experience in SRE, observability, or backend systems, especially when paired with strong AI/ML depth

• Experience with RLHF, synthetic data pipelines, or LLM evaluation tooling

• Contributions to open-source agent frameworks such as LangGraph, DSPy, or similar

• Research experience in LLMs, agents, or reinforcement learning, including publications in venues such as NeurIPS, ICML, or ICLR; top-tier conference publications are a plus

Compensation

We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $160,000–$300,000, plus equity and benefits. Our salary ranges are based on location, level, and role. Individual compensation is determined by experience, skills, and job-related knowledge.

Why You Should Join Us

Traversal is a place to take on hard, meaningful problems with real ownership from day one. You’ll work alongside people who challenge you to grow, learn constantly, and help define a new category of infrastructure software. We think long term, move quickly, and hold a high bar without taking ourselves too seriously.

We offer competitive salary and equity packages, health insurance, fertility benefits, a great tech setup stipend and flexible time off. Plus in-office snacks, team happy hours and outings, an annual company offsite, and plenty of built in time to collaborate across teams.

Traversal is fully in-office, 5 days a week, based in New York near Madison Square Park. We have a collaborative, hard-working culture and are energized by building the future of AI-powered software maintenance.