Location

This is a hybrid role based in the United States that requires in-person work at our Bellevue, Washington office three days per week on Tuesday, Wednesday, and Thursday.

Our office is located at:
US Bank Plaza
10800 NE 8th Street, Suite 210
Bellevue, WA 98004
The Opportunity

As a Senior Forward Deployed Engineer, you sit where platform engineering meets AI. You bring deep Kubernetes expertise to help enterprises adopt Stacklok's Enterprise platform and run AI agents securely on the infrastructure they already trust.

This is hands-on, high-ownership work. You will lead full forward-deployed engagements end to end, stand up custom proof-of-concepts with Design Partners, and answer the hard technical questions that come up as customers move toward production. When unlocking value means changing how the product deploys to Kubernetes, you own that work and contribute the changes back to Stacklok Enterprise itself.

Demand for this work is outpacing the team's capacity, so you will have a front-row seat to how leading enterprises put AI into production, and real influence over what gets built next. If you want your platform expertise to land directly with customers, this is your opportunity to do it at the frontier of enterprise AI.
What Success Looks Like: First 6-12 Months

• Ramped quickly on the platform and Stackok Enterprise architecture, becoming the technical SME the AppliedAI team relies on for enterprise engagements.
• Built trusted relationships across the team and with customers, and resolved a real customer blocker or shipped a first meaningful change.
• Took one or more Design Partners from proof-of-concept to a working production deployment of Stacklok's Enterprise platform.
• Unblocked enterprise adoption by improving how the product deploys to Kubernetes, measurably cutting time-to-value for customers.
• Turned field learnings into a reusable engagement playbook and tooling, using AI-assisted workflows to make the next deployment faster for the whole team.

In This Role, You Will

• Drive forward-deployed engagements end to end, from scoping each customer's technical goals and designing the deployment approach to taking POCs to a working state and toward production.
• Design and deliver changes to the platform and to how it deploys to Kubernetes, unblocking enterprise adoption and contributing those changes back to Stackok Enterprise.
• Act as the technical SME for enterprise adoption, answering deep platform and Kubernetes questions and giving hands-on support to customers and Design Partners.
• Own the technical calls within your domain, moving quickly on reversible decisions and pulling in the team anchor as scope and risk grow.
• Partner with senior peers and bring field insight back through standup, planning, and design reviews to influence priorities and how engagements run.
• Coach teammates in your areas of deep expertise, especially Kubernetes, and contribute to hiring when needed.
• Apply AI-assisted workflows and strengthen reusable tooling and playbooks so each engagement moves faster for the team.

Desired Skill & Experience

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.

• Deep Kubernetes expertise across cluster architecture, workload types, networking, storage, RBAC, and resource management, with the ability to design and debug permission models.
• Strong operator and CRD literacy: reasons about control loops, CRD versioning, status, and finalizers, and writes controllers in Go using Kubebuilder or the Operator SDK.
• Proven experience deploying into managed Kubernetes, fluent in how it meets cloud infrastructure (IAM, networking, storage), with Helm authoring and GitOps via Flux or ArgoCD.
• Comfortable working directly with customers, including over-the-shoulder debugging across varied enterprise permission models, and clearly communicating root causes and remediation steps.
• Solid grasp of observability across metrics, logs, and traces, and when each applies. Familiarity with Prometheus, OpenTelemetry, and platforms like Datadog or Grafana is a plus.
• A track record of delivering production-grade systems and contributing fixes back to the products you support. Hands-on experience with MCP servers or AI agent tooling is a strong plus.
• AI-first mindset: an active user of AI coding assistants who brings agentic workflows (skills, agents, rules, hooks) 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 intrinsic motivation: self-directed and hands-on, thrives in fast-moving, ambiguous environments, and drives clarity through action.

#LI-Hybrid