About Spectro Cloud
We are looking for a Sr. Forward Deployed Solution Engineer (FDSE) who is equally comfortable writing automation, troubleshooting a production Kubernetes cluster, whiteboarding a GPU fabric, and working with Customer leaders to be the tip of our FDE practice and guide the Customer to successful technical and business outcomes. You will join the FDE team and at the point with our Customer(s) where business or mission goals meet technical reality. You will translate desired outcomes into deployable architectures, build the automation and integrations needed to make those architectures real, and guide each deployment from first working capability through production readiness, scaled adoption, and operational handoff and working closely with our other FDE practice resources and the aligned Deployment Strategist. This is hands-on engineering not traditional staff augmentation, and not a role where the work ends with a slide deck or demo. You will work across Palette / PaletteAI, Kubernetes, cloud, bare metal, edge, GPU systems, data pipelines, high-performance networking, and the NVIDIA software and hardware ecosystem. You will also bring what you learn back into Product and Engineering so that the next deployment is faster, more standardized, and easier for our FDE teams and Customers to operate independently. The best candidates enjoy ambiguity, learn quickly, communicate directly, and care deeply about the difference between technology that is installed and capability that is genuinely useful.
About You
You thrive where the problem is important, the environment is complex, and the path is not yet fully defined. You can move between code, infrastructure, networking, user workflows, architectural reviews and guidance with other FDE team members, and Customer conversations without losing the thread of the outcome. You are curious without being careless, confident without pretending to know everything, and pragmatic without accepting permanent shortcuts. You communicate early when risk changes, write down what others will need later, and know that the best technical solution is one the customer can operate successfully. We do not expect one person to have deployed every product and technology outlined in this description. We do expect deep Kubernetes and automation capability, strong systems reasoning, customer-facing judgment, and the ability to become productive quickly in unfamiliar parts of the stack.
Required qualifications
● Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related technical field, or equivalent practical experience.
● 6+ years of professional experience in software engineering, platform engineering, site reliability engineering, DevOps, infrastructure engineering, solutions engineering, or a comparable customerfacing technical role.
● Production experience designing, deploying, upgrading, and troubleshooting Kubernetes clusters and cloud-native applications.
● Strong Linux and distributed-systems fundamentals, including processes, networking, storage, identity, certificates, resource management, and failure analysis.
● Proficiency in at least one modern programming language preferably Go or Python and the ability to produce maintainable, tested, production-quality code.
● Hands-on experience with infrastructure as code and configuration automation using technologies such as Terraform, Ansible, Cluster API, Helm, Kustomize, and equivalent tools.
● Experience implementing CI/CD or GitOps workflows using platforms such as GitHub Actions, GitLab CI, Jenkins, Argo CD, Flux, or comparable systems.
● Working knowledge of Kubernetes security and multi-tenancy, including RBAC, namespaces, network policy, admission controls, quotas, secrets, pod security, and tenant isolation.
● Experience with at least one major public cloud and at least one datacenter deployment model such as bare metal, VMware, KubeVirt, Proxmox, or OpenStack.
● Working knowledge of…