Founding Engineer, Real-Time AI Runtime

uRun; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity

Health, dental, and vision

401(k)

FSA/HSA

Paid time off

Top-tier tooling

MacBook Pro and AirPods

Job summary

uRun is building a universal runtime for real-time, stateful AI inference. We seek a senior engineer to design and own the scalable, low-latency infrastructure powering live, multi-user AI workloads. You’ll drive latency, memory usage, and QoS as a hands-on technical leader reporting to the founder.

You’ll shape platform standards, mentor engineers, and partner with ML and video teams to push the boundaries of real-time AI infrastructure in a fast-paced startup.

Qualifications

• 7+ years of engineering with a track record architecting and owning large-scale production systems.
• Deep Kubernetes expertise, including GPU-heavy clusters and service-mesh patterns.
• Strong cloud and infrastructure-as-code: AWS, GCP, or Azure; Terraform, Pulumi; networking and security (VPC, IAM, API-gateway-style routing).
• SRE-style thinking and observability depth: Prometheus/Grafana, OpenTelemetry, tracing, SLOs, incident response, post-mortems.
• Proficiency in at least one of Python, Go, or TypeScript/Node.js for platform tooling, automation, and glue code.
• Experience with streaming or real-time systems: WebRTC, low-latency video pipelines.
• Track record mentoring engineers and influencing cross-functional teams.

Responsibilities

• Design, operate, and evolve the cloud-native platform that runs uRun’s real-time inference and video runtime, Kubernetes, GPU-heavy workloads, and streaming pipelines.
• Own observability, reliability, and performance at scale: SLO-driven capacity, autoscaling, failover, and cost-efficient GPU provisioning.
• Build and maintain the platform primitives that product and ML teams depend on, service meshes, deployment pipelines, secrets and credential management, and configuration-as-code.
• Partner closely with ML and video-workload engineers to optimise for low-latency inference, memory-bound workloads, and streaming data flows.
• Define and champion platform standards for security, observability, and incident response, drawing on SRE-style practices.
• Mentor and unblock other engineers, and act as a technical leader on architecture, trade-offs, and long-term platform evolution.

Skills

Kubernetes expertise

GPU workloads

Cloud infrastructure as code

SRE and observability

Python/Go/TypeScript

Streaming/real-time systems

Mentoring engineers

Tools

Terraform

Pulumi

OpenTelemetry

Prometheus/Grafana

Job description

uRun is building a universal runtime for real-time, stateful AI inference. We seek a senior engineer to design and own the scalable, low-latency infrastructure powering live, multi-user AI workloads. You’ll drive latency, memory usage, and QoS as a hands-on technical leader reporting to the founder.

You’ll shape platform standards, mentor engineers, and partner with ML and video teams to push the boundaries of real-time AI infrastructure in a fast-paced startup.