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Ai Traffic Engineer Jobs (NOW HIRING)

VHB

Traffic Engineering Project Manager

Hauppauge, NY · Hybrid

$120K - $170K/yr

Professional Engineer (P.E.) licensure required * Understanding of Vissim and Synchro preferred ... Learning and development supported by evolving tools and technologies, including AI * Best-in-class ...

VHB

Traffic Engineering Project Manager

Hauppauge, NY · On-site

$120K - $170K/yr

Professional Engineer (P.E.) licensure required * Understanding of Vissim and Synchro preferred ... Learning and development supported by evolving tools and technologies, including AI * Best-in-class ...

Eridu AI

Network Simulation Engineer

Saratoga, CA · On-site

... optimized AI traffic flows. * Tool Development & Partnership: Interface with simulation tool ... MSc or PhD in Computer Science, Electrical Engineering, or a related field with some specialization ...

VHB

Traffic Engineering Project Manager

Hauppauge, NY · Hybrid

$120K - $170K/yr

Professional Engineer (P.E.) licensure required * Understanding of Vissim and Synchro preferred ... Learning and development supported by evolving tools and technologies, including AI * Best-in-class ...

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All JobsAi Traffic Engineer Jobs

Ai Traffic Engineer information

See salary details

$45.5K

$102.9K

$141K

How much do ai traffic engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for ai traffic engineer in the United States is $102,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,000.00 and $118,500.00 per year, depending on experience, location, and employer.

How does an AI traffic engineer typically collaborate with urban planners and civil engineers on smart city projects?

AI Traffic Engineers often work closely with urban planners and civil engineers to design and implement intelligent traffic management systems. This collaboration involves translating transportation needs into data-driven solutions, integrating AI algorithms with existing infrastructure, and participating in interdisciplinary meetings to align technical capabilities with urban development goals. Effective communication and teamwork are essential, as AI Traffic Engineers must ensure their models support broader city planning initiatives while addressing real-time traffic challenges. This collaborative environment fosters innovation and offers opportunities to expand expertise in both AI and urban development.

What is an AI traffic engineer?

AI Traffic Engineers are professionals who use artificial intelligence and machine learning technologies to optimize and manage transportation systems. They analyze data from various sources, such as sensors, cameras, and GPS devices, to improve traffic flow, reduce congestion, and enhance safety on roads. Their work can involve designing smart traffic signals, developing predictive models for traffic patterns, and implementing autonomous vehicle infrastructure. AI Traffic Engineers collaborate with city planners, software developers, and transportation authorities to create more efficient and sustainable urban mobility solutions.

What is the difference between Ai Traffic Engineer vs Traffic Data Analyst?

AspectAi Traffic EngineerTraffic Data Analyst
Required CredentialsBachelor's in Traffic Engineering, Computer Science, or related field; knowledge of AI and traffic systemsBachelor's in Data Analysis, Statistics, or related field; proficiency in data tools
Work EnvironmentTraffic management centers, urban planning agencies, tech companiesResearch labs, government agencies, consulting firms
Industry UsageDesigning AI-driven traffic solutions, optimizing flow, reducing congestionAnalyzing traffic patterns, reporting insights, supporting planning decisions

The Ai Traffic Engineer focuses on developing and implementing AI-based traffic management systems, requiring technical expertise in AI and traffic engineering. In contrast, the Traffic Data Analyst primarily interprets traffic data to inform decisions. Both roles involve data analysis but differ in technical scope and application.

What are the key skills and qualifications needed to thrive as an AI traffic engineer, and why are they important?

To thrive as an AI Traffic Engineer, you need a strong background in transportation engineering, data analysis, and machine learning, typically supported by a degree in civil engineering, computer science, or a related field. Proficiency with traffic simulation software (like VISSIM), programming languages (such as Python), and familiarity with AI frameworks and data visualization tools are essential. Problem-solving, collaboration, and effective communication skills help you translate complex technical concepts to stakeholders and work with multidisciplinary teams. These skills and qualities are critical for developing innovative traffic solutions that optimize flow, enhance safety, and improve urban mobility.
More about Ai Traffic Engineer jobs
What cities are hiring for Ai Traffic Engineer jobs? Cities with the most Ai Traffic Engineer job openings:
What states have the most Ai Traffic Engineer jobs? States with the most job openings for Ai Traffic Engineer jobs include:
What job categories do people searching Ai Traffic Engineer jobs look for? The top searched job categories for Ai Traffic Engineer jobs are:
Ai Traffic Engineer jobs near you
Infographic showing various Ai Traffic Engineer job openings in the United States as of August 2026, with employment types broken down into 83% Full Time, 11% Part Time, and 6% Contract. Highlights an 72% In-person, 6% Hybrid, and 22% Remote job distribution, with an average salary of $102,947 per year, or $49.5 per hour.

Backend Engineer, AI (Agent Systems)

Bjak

Charleston, WV • Remote

Full-time

Re-posted 15 days ago

Job description

About A1

There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.

Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.

 
Role

As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience.

You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients.

 
Focus

  • Build and operate backend systems that serve AI-powered features in production.

  • Design inference pipelines, orchestration layers, and service boundaries around models.

  • Own production concerns: monitoring, logging, alerting, and incident response.

  • Optimize latency and throughput across inference, caching, batching, and streaming.

 
Ideal Experiences

  • Strong backend engineering fundamentals in production environments.

  • Experience running high-throughput, low-latency services.

  • Familiarity with AI inference patterns (LLMs, embeddings, multimodal).

  • Comfortable debugging distributed systems under load.

  • Bias toward shipping and learning from production behavior.

 
Outcomes

  • Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.

  • APIs are stable, clear, and support seamless integration with frontend and ML systems.

  • Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact.

  • Iterative improvements based on real usage continuously increase system performance and reliability.

 
Tech Stack

  • Python

  • NodeJs

  • Pytorch

  • OpenAI / Anthropic / open-source LLMs

  • SQl & noSQL

  • Kubernetes

  • Docker

 
How We Work

The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product

 
Interview process

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.