We are seeking a seasoned Backend Tech Lead with a solid background in high-load environments and experience in managing multiple Linux servers. The ideal candidate is someone who thrives in a fast-paced, innovative, and technology-driven culture.
Responsibilities:
Own architecture for high-scale, user-facing backends and data pipelines.
Lead and mentor engineers; guide design reviews, roadmaps, and execution.
Operate production systems with clear SLOs/SLAs, on-call quality, and blameless postmortems.
Evolve our K8s/GPU platform, CI/CD, and observability to increase deployment velocity and resilience.
Integrate and serve ML models (PyTorch, CUDA/TensorRT, Triton) with a focus on throughput and cost.
Partner cross-functionally (ML, Product, Security, Finance) on priorities and cost/perf trade-offs.
Hire, level up the team, and uplevel engineering standards.
Responsibilities:
Own architecture for high-scale, user-facing backends and data pipelines.
Lead and mentor engineers; guide design reviews, roadmaps, and execution.
Operate production systems with clear SLOs/SLAs, on-call quality, and blameless postmortems.
Evolve our K8s/GPU platform, CI/CD, and observability to increase deployment velocity and resilience.
Integrate and serve ML models (PyTorch, CUDA/TensorRT, Triton) with a focus on throughput and cost.
Partner cross-functionally (ML, Product, Security, Finance) on priorities and cost/perf trade-offs.
Hire, level up the team, and uplevel engineering standards.
Requirements:
7+ years backend engineering, including 2+ years tech-leading or managing.
Deep experience in Node.js or Python (strong in the other).
Distributed systems/Kubernetes/cloud expertise; strong operational rigor.
Track record of scaling systems, improving reliability, and shipping fast.
Excellent communication, prioritization, and mentoring skills.
Nice to have:
Large K8s clusters (hundreds of nodes), GPU scheduling, NVIDIA stack (CUDA, Triton).
7+ years backend engineering, including 2+ years tech-leading or managing.
Deep experience in Node.js or Python (strong in the other).
Distributed systems/Kubernetes/cloud expertise; strong operational rigor.
Track record of scaling systems, improving reliability, and shipping fast.
Excellent communication, prioritization, and mentoring skills.
Nice to have:
Large K8s clusters (hundreds of nodes), GPU scheduling, NVIDIA stack (CUDA, Triton).
This position is open to all candidates.
