Senior AI Deployment Lead - GPU, Serverless & Enterprise

PT Sea Group; Indonesia; On-site; IDR 500,000,000 - 900,000,000; Full time

Job summary

SeaCloud is seeking a Lead Forward Deployed Engineer to spearhead complex customer engagements across model APIs, GPU VMs, and bare metal GPU clusters. You will guide discovery, architecture, and delivery while coordinating across SeaCloud and customer teams to achieve production readiness.

You will lead performance validation, on-call readiness, and handover, ensuring successful production adoption and scalable outcomes for enterprise AI workloads.

Qualifications

• 6+ years of relevant engineering experience with customer-facing production systems.
• Strong Linux, networking, containers, Kubernetes, storage, and observability fundamentals.
• Strong Python and shell scripting skills.
• Production experience with GPU-backed AI workloads.
• Experience with GPU memory sizing and multi-GPU performance.
• Willingness to travel for customer workshops and critical launch phases.

Responsibilities

• Own complex customer engagements as primary technical owner.
• Lead discovery to uncover objectives, workloads, targets, security needs, budgets, constraints.
• Translate requirements into scoped delivery plans with milestones and ownership.
• Lead architecture reviews, workshops, progress discussions, and customer-facing incident communication.
• Drive onboarding and integration of enterprise AI apps into customer environments.
• Design or review Kubernetes deployment patterns and customer orchestration needs.
• Lead performance validation, benchmarking, and acceptance activities.
• Coordinate incident response and handover with Support, SRE, and Infra teams.

Skills

Linux

Networking

Containers

Kubernetes

Storage

Observability

Distributed systems

Python

Shell scripting

GPU AI workloads

GPU memory sizing

Job description

SeaCloud is seeking a Lead Forward Deployed Engineer to spearhead complex customer engagements across model APIs, GPU VMs, and bare metal GPU clusters. You will guide discovery, architecture, and delivery while coordinating across SeaCloud and customer teams to achieve production readiness.

You will lead performance validation, on-call readiness, and handover, ensuring successful production adoption and scalable outcomes for enterprise AI workloads.