Senior Forward Deployed Engineer

About the role

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 cau

Additional Information

Stacklok is led by CEO Craig McLuckie and CTO Joe Beda , two of the creators of Kubernetes. As AI reshapes how software is built and used, we're building the foundation enterprises need to adopt it with confidence. We're building the control plane for enterprise AI agents, enabling organizations to run, govern, and secure them on the infrastructure they already trust. Through Model Context Protocol (MCP) servers running across Kubernetes and private cloud environments, AI agents can securely connect to internal data and systems while meeting the security, compliance, and operational requirements of highly regulated and security-conscious organizations. We've also extended this foundation to the model layer with an enterprise AI gateway. The Stacklok Enterprise Platform is built on ToolHive , our open source MCP platform, and is already being adopted by leading technology companies and organizations in regulated industries. We also help maintain the official MCP registry and contribute openly to the community shaping the future of enterprise AI. 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

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at stacklok? Share your experience