Technical Customer Support Engineer Tier 3

UVeye•Teaneck, NJ

2d•Onsite

About The Position

At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of vehicle inspection systems. At the heart of this innovation lies our advanced AI-centric technology, representing the pinnacle of computer vision, machine learning, and generative AI within the automotive sector. With over $380M in funding and strategic partnerships with industry giants such as Toyota, Amazon, General Motors, Volvo, and Hertz, our technology is utilized in manufacturing plants, dealerships, wholesale auctions, delivery fleets, seaports, and more. Our growing global team of 250+ employees is committed to creating a workplace that celebrates diversity, encourages teamwork, and strives for excellence. We’re looking for a Technical Customer Support Engineer Tier 3 for our Teaneck, NJ office to serve as the highest level of technical escalation for complex software, infrastructure, and system integration issues impacting UVeye’s inspection platforms. This role requires expertise in distributed systems, Linux environments, containerized applications, cloud infrastructure, and networking, along with the ability to perform advanced troubleshooting, root cause analysis, and cross-functional collaboration with Engineering, DevOps, and R&D teams to drive scalable, long-term solutions.

Requirements

3+ years of experience in advanced Technical Support (Tier 3), Systems Engineering, DevOps, or Site Reliability Engineering (SRE), ideally within a SaaS, IoT, or hardware/software integrated environment.
Deep, hands-on proficiency with Linux environments and advanced command-line troubleshooting.
Extensive experience managing, deploying, and troubleshooting applications using Docker and Kubernetes.
Strong understanding of advanced networking concepts (TCP/IP, HTTP, DNS, DHCP, routing, firewalls, and load balancers).
Proficiency in scripting languages (Bash, Python) for system automation and log analysis.
Operational understanding/experience with major cloud platforms (AWS, Azure, or GCP).
High comfort level operating within ticketing and CRM systems like Jira Service Management, Github and Salesforce.
Strong analytical problem-solving skills, ability to remain calm under pressure, and a team-oriented, customer-first mindset.

Nice To Haves

Experience with deployment and Infrastructure as Code (IaC) tools such as Jenkins and Helm.
Background in machine vision, or AI-driven SaaS platforms.
Experience in a startup environment.
Experience supporting multi-functional Revenue organizations
Background working within SaaS, Automotive Technology, or Enterprise Hardware + Software environments
Familiarity with CRM and enablement platforms (Salesforce, LMS, knowledge systems)
Ability to translate technical product capabilities into business and operational outcomes
A builder mindset with comfort operating in high-growth environments

Responsibilities

Serve as the final escalation point for Tier 2 Support Engineers, Field Service Engineers (FSEs), and Customer Success Managers (CSMs), resolving the most complex and critical system incidents.
Perform advanced root-cause analysis (RCA) on intricate hardware/software interoperability issues, diagnosing problems across Linux operating systems, containerized environments (Docker/Kubernetes), and cloud platforms (AWS/GCP).
Work directly with Product, R&D, and DevOps teams to replicate persistent bugs, test software patches, and provide vital feedback on system stability and architecture.
Adopt a "System Builder" mindset by writing custom scripts (Python, Bash) to automate repetitive tasks and implement automated monitoring tools, reducing manual support overhead.
Analyze log files and network traffic to identify bottlenecks or failures in data pipelines and local IoT hardware setups.
Create and standardize Standard Operating Procedures (SOPs) and technical documentation.
Mentor and train Tier 1/2 agents to empower them to solve issues autonomously and improve first-touch resolution rates.