Stacklok - Staff Forward Deployed Engineer - Kubernetes
Requirements
• We do not expect every candidate to meet every point below. If this role excites you and you bring most of it, we encourage you to apply. • Strong software engineering fundamentals: writes well-structured production code with sound design and testing judgment. • Extensive experience serving as the senior or lead engineer in enterprise customer engagements, with a proven ability to lead hands-on customer delivery in the field. • Proven technical leadership through technical direction, mentorship, and stewardship of high-quality engineering practices. • Deep Kubernetes expertise across cluster architecture, networking, storage, RBAC, and permission models, with operator and CRD literacy, Go controllers, Helm authoring, and GitOps via Flux or ArgoCD. • Strong observability expertise across metrics, logs, and traces, with the ability to instrument, troubleshoot, and debug production systems using Prometheus, OpenTelemetry, Datadog, or Grafana. • Hands-on experience building or running MCP servers or AI agent tooling, ideally in production environments. • AI-first mindset: an active user of AI coding assistants who brings agentic workflows into daily work and experiments with AI to automate and accelerate delivery. • Communication: excellent written and verbal communication, able to explain complex technical ideas clearly to both technical and non-technical audiences. • Startup mentality and strong ownership: self-directed and hands-on, comfortable building where no playbook exists yet, and driving clarity through action rather than waiting for it.
Responsibilities
• Lead forward deployed engagements across APAC end to end, from scoping each customer's technical goals and deployment approach through to a working production deployment. • Own the region's technical calls as the in-region anchor and escalation point for the hardest platform and Kubernetes problems customers raise. • Design and deliver changes to how the platform deploys to Kubernetes, unblocking enterprise adoption and contributing those changes back upstream. • Define the reusable reference architectures and deployment patterns that engagements across the region and the wider team build on. • Set the technical bar for APAC, mentoring engineers through design reviews and pairing and serving as the technical gate for what good looks like in hiring. • Own how forward deployed work runs in the region, adapting it to how local customers operate and shaping where it hands off to applied AI engineering. • Establish the AI-assisted practices and tooling the team adopts, and channel APAC field insight into the product roadmap.
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