Traversal

Traversal

AI Engineer - Backend/Platform

New York · Full-time

Sponsorship not specified$150k-$300kDetected 102 days ago
ExpressDistributed SystemsBackend DevelopmentDatadogSite Reliability EngineeringLLMsAgentic AIAI OrchestrationResearchCommunication

Stay score

odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level II · 2×
Level I$109,8451 entry
Level II$137,7172 entries
Level III$165,5893 entries
Level IV$193,4614 entries

$15,589 more — $165,589 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $165,589 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · New York-Newark-Jersey City, NY-NJ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

No reports yet — be the first to help the next applicant.

About the role

  • As an AI Engineer - Backend/Platform at Traversal, you'll work on the core foundations that make Traversal's AI possible while ensuring Traversal's platform, products, and applications are delivered with a high bar for quality, reliability, resilience, cost-effectiveness, and maintainability.
  • You will build and own the frameworks, shared libraries, application foundations, observability, and developer tooling that power Traversal's systems and AI agents.
  • This involves designing scalable distributed systems and abstractions, delivering core application framework components, implementing best practices for software architecture and software delivery while balancing velocity, research flexibility, and production reliability.

Responsibilities

  • Lead the design and implementation of scalable, robust backend systems to support AI agents and observability tools.
  • Design and implement high-performance APIs to enable seamless communication between backend systems and frontend interfaces.
  • Architect scalable distributed systems to support real-time workloads over petabytes of heterogeneous telemetry data.
  • Build live evaluation pipelines, automated scoring systems, and benchmarks to measure and drive AI performance.
  • Collaborate with AI engineers and scientists to integrate AI-driven insights and solutions into backend systems.
  • Monitor, optimize, and scale backend services to handle high volumes of data while ensuring low-latency performance.
  • 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.
  • We have a collaborative, hard-working culture and are energized by building the future of AI-powered software maintenance.

Requirements

  • Proven production-scale software engineering experience.
  • Experience with LLM-based applications and/or multi-agent systems.
  • Strong data modeling skills and a track record of writing clean, maintainable code.
  • Collaborative, impact-driven mindset and ability to work across research and engineering teams.

Nice to have

  • Knowledge of software incidents and production SRE workflows.
  • Prior experience with AI benchmarking or evaluation systems.
  • Experience creating quantitative scoring systems or benchmarks in new problem domains.
  • Familiarity with observability stacks (logs, metrics, traces) and telemetry systems.
  • Background in agentic architectures, orchestration frameworks, or applied AI research.
  • 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.

Skills

  • About Traversal
  • Today, Traversal operates in mission-critical environments at some of the world's largest enterprises.
  • Traversal is backed by Sequoia Capital, Kleiner Perkins, Hanabi, NFDG, and American Express Ventures.

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 $150,000-$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.
  • 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.

Company info

  • Our mission is to free engineers from endless firefighting and give them more time to focus on creative, high-impact work.

This listing is sourced directly from Traversal's careers page and normalized into a canonical job model.