What You'll Own
Lead deployments of Dynamo AI products into customer environments: EKS, AKS, GKE, OpenShift, and on-prem Kubernetes clusters
Work directly with customer engineering, security, infrastructure, and operations teams across networking, identity, storage, observability, scaling, security, and reliability
Troubleshoot production and pre-production issues across Kubernetes, application services, databases, ingress, authentication, networking, and cloud infrastructure
Build deployment automation, Helm configurations, scripts, runbooks, and validation workflows
Drive technical scoping, effort estimation, risk assessment, rollout planning, and production readiness reviews
Partner with product and engineering teams to surface deployment patterns, integration gaps, and customer-driven improvements
Requirements
Must-Have
3-8 years post-undergrad in software engineering, infrastructure engineering, platform engineering, solutions engineering, or customer-facing engineering (1+ year post-grad with master's also acceptable)
Strong hands-on Kubernetes production experience plus at least one major cloud (AWS, Azure, or GCP)
Infra engineer or DevOps background at a startup, solutions company, or consulting firm. Traditional DevOps from banks or other "traditional sector" companies is a hard exclusion per the hiring manager.
Customer-facing deployment experience: comfortable interfacing with customer engineering, security, and compliance teams
Comfortable with East Coast US or UK time zones, with availability for twice-weekly evening calls to collaborate with the India team
Nice-to-Have
Master's or beyond in Computer Science, Engineering, or related field
Familiarity with Generative AI systems, LLM applications, AI infrastructure, or model deployment workflows
Experience working in financial services, healthcare, government, or other regulated industries
Identity and access systems experience (OIDC, SAML, Keycloak, Entra ID, Okta)
AI evaluation, guardrails, observability, or monitoring systems background
Prior FDE, Solutions Engineering, or Implementation Engineering at a high-growth AI infrastructure or AI tooling startup
Salary :
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