AI Research Engineer

Traversal•New York, NY

5d•$180,000 - $300,000•Onsite

About The Position

Traversal is the AI Site Reliability Engineer (SRE) for the enterprise—already trusted by some of the largest companies in the world to troubleshoot, remediate, and even prevent the most complex production incidents. Our mission is to free engineers from endless firefighting and enable them to focus on creative, high-impact work. Our roots remain deeply embedded in AI research, and we’re channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. Hence, what we’re proudest of is assembling the most talented yet nicest group of individuals, including researchers from MIT, Harvard, and Berkeley, to world-class engineers from industry: Citadel Securities, Cockroach Labs, Datadog, DE Shaw, ServiceNow, Glean, Perplexity, Pinecone, and more, to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible.

Requirements

5+ years of software engineering experience, with a strong focus on backend development and experience building scaled systems.
Hands-on experimentation experience — running experiments, evaluating results, and iterating on them. Side projects and personal work count.
Proven ability to lead in fast-paced startup environments, with limited resources, shifting priorities, and minimal structure.
Strong experience with Python and web frameworks such as FastAPI.
Experience deploying applications on AWS, working with ECS or Kubernetes, Postgres for data storage, and S3 for large-scale object storage.
Familiarity with observability and monitoring tools to ensure the system is running smoothly and efficiently.

Nice To Haves

A research engineer background, or prior experience as the engineer embedded in a research team.
Experience building or operating agentic AI systems.
Background in large-scale, complex, data-driven applications.
Familiarity with AI or LLM-powered products, and with evaluation or benchmarking tooling.

Responsibilities

Build and scale the infrastructure behind the team's research — experiment harnesses, evaluation pipelines, and trajectory tooling — so that ideas can be tested quickly and results can be trusted.
Take promising research prototypes and make them fast, reliable, and production-ready, closing the gap between a one-off experiment and a capability that ships to enterprise customers.
Partner with researchers to design experiments — framing the hypothesis, choosing the measurement, and making sure the result is real before it drives a decision.
Work closely with AI engineers, infrastructure teams, and product leads to bring research into production and close the loop between experimentation and impact.
Track developments in LLMs, agent architectures, and evaluation methodology, translating insights into actionable improvements for Traversal's domain.
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.