Location: New York, NY

Work Model: Hybrid / flexible

Industry: AI security & infrastructure (Model Context Protocol)

Compensation: ~$180K base, plus performance bonus

About the Company

Our partner is an early-stage, fast-scaling startup building security infrastructure for the Model Context Protocol, protecting enterprises from data leaks as they adopt AI agents. Founded less than a year ago, they already have a multi-million-dollar pipeline, a deeply technical product, and backing from top-tier investors. The bar is high, the pace is fast, and the problems are genuinely hard.

The Opportunity

As the Founding Support Engineer, you will build the support function from scratch for enterprise customers deploying AI infrastructure. You will sit at the intersection of engineering and customers, debugging hard technical problems, defining how support runs, and making enterprise customers successful post-sale.

This is a technical, customer-facing seat for someone who is both an excellent engineer and genuinely comfortable in front of people. You will join an established, professional team rather than a first-engineer situation, with rapid advancement and leadership possible within 6-12 months.

Responsibilities

Own technical support for enterprise customers deploying the product, async and over Slack/Teams
Debug issues across Python/TypeScript, PostgreSQL, HTTP requests, and Kubernetes pod logs
Troubleshoot enterprise identity (SSO, SCIM, OAuth) and cloud infrastructure, primarily AWS (EKS/ECS, CloudWatch, VPCs)
Define SLAs, triage workflows, and escalation paths from zero to one
Serve as the technical bridge between customers and the engineering team
Build support tooling and documentation that reduce ticket volume over time

Requirements

4-6 years as an engineer, support engineer, solutions engineer, or developer success advocate; exceptional candidates with less experience considered
Strong technical depth in enterprise infrastructure and AI systems, with experience supporting large enterprises
Strong computer science or statistics foundation
Startup or consulting background with real time in front of customers
AI-native: uses MCPs and AI tools daily, with excellent written communication and a customer-first mindset
Consistent tenure without a pattern of short stints
Bonus: hands-on MCP or agent tool-calling in production, or security-critical / compliance-driven enterprise deployments