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Runlayer is building an enterprise platform for AI Agents, MCPs (Model Context Protocol), and Skills with built-in security, governance, and observability. The company recently raised $30M Series A (total $42M) and is trusted by Gusto, Instacart, Opendoor, dbt Labs, and Decagon.
As the founding Support Engineer, you will be the technical frontline for enterprise customers deploying Runlayer across their engineering organizations. You'll work directly with customers via Pylon, Slack, and Teams to triage and resolve issues spanning the control plane, MCP connectors, OAuth flows, deployment configurations, and AI client integrations. This is a zero-to-one role where you'll build the support function from scratch, establishing playbooks, runbooks, and escalation paths.
Key responsibilities include:
- Triaging and resolving technical issues across the platform stack (control plane, connectors, OAuth, deployments)
- Using AI and MCP tooling to accelerate diagnostics and troubleshooting
- Guiding enterprise teams through onboarding (SSO, SCIM, connector activation, policy configuration)
- Building knowledge base from zero: runbooks, troubleshooting guides, and customer-facing documentation for common deployment patterns (EKS, ECS, Helm, Terraform)
- Managing escalations with clear reproduction steps to Platform, SRE, or Identity engineers
- Closing feedback loops between customers and product/engineering to drive doc fixes, product improvements, and self-serve flows
- Learning and communicating new features as they ship weekly
You'll work closely with the engineers who built the platform and use AI tooling daily. The role offers direct impact with enterprise customers, ownership of the entire support function, and the opportunity to shape how a fast-growing AI infrastructure company scales customer success.
REQUIREMENTS:
- 3–5 years in technical support, solutions engineering, or customer-facing engineering at SaaS or developer-tools companies
- Infrastructure support background or strong technical depth in enterprise infrastructure and AI systems (agents, identity)
- Debugging fluency across the stack: Python/TypeScript reading, PostgreSQL queries, HTTP request tracing, Kubernetes pod log interpretation
- Familiarity with enterprise identity (SSO, SCIM, OAuth) and cloud infrastructure (AWS preferred: EKS/ECS, CloudWatch, VPCs)
- Experience running support in Pylon and over Slack or Teams
- AI-native workflow: daily use of MCPs and AI tools for real work
- Strong written communication for both engineers and IT admins
- Zero-to-one mindset: comfortable defining SLAs, triage workflows, and escalation paths
BONUS:
- Hands-on MCP experience and understanding of how agents call tools in production
- Experience supporting security-critical or compliance-driven enterprise deployments
- Track record building support tooling or self-serve flows that measurably reduced ticket volume
