Principal AI Solutions Architect

We're a venture-backed cloud infrastructure company (founded 2017, valued at $1B in our most recent round) building the application networking layer that runs underneath some of the largest enterprises in the world. Our platform handles API management, service mesh, and ingress/egress for production workloads at massive scale — built on Envoy, Istio, Kubernetes, and eBPF, with deep contributions back to the open-source projects we depend on.

The reason this role exists: our customers are now running real AI workloads on top of us — LLM gateways, agent-to-agent traffic, multi-tenant model serving — and they need someone who can architect that layer with them, not just answer tickets about it. That's you.

The work

You'll be the technical owner for a small portfolio of strategic accounts — typically large enterprises with production environments that matter. "Owner" means you know their architecture, their team, their roadmap, and their failure modes better than anyone else at our company. You're the person they call when something's on fire, and also the person they call before they decide to build something new.

Specifically:

• Architect their AI infrastructure layer. LLM gateways with auth, rate limiting, and observability. Agent-to-agent communication patterns. Securing inference traffic across multi-cloud environments. Most of our customers haven't done this before — you have, or you'll figure it out alongside the engineering team and write the playbook everyone else uses.
• Run technical issue resolution end-to-end. When something escalates, you partner with Support and Engineering, drive root cause, and often dig in directly. We expect Principal-level architects to get their hands dirty when it accelerates the outcome — reading code, reproducing issues, writing reference implementations.
• Drive deep adoption. You'll consult on performance tuning, deployment patterns, and operational best practices. You'll spot new use cases inside the account and bring them forward.
• Influence the product. You sit closer to real production AI workloads than almost anyone in the company. Product Management and Engineering treat your feedback as a primary signal for the roadmap.
• Partner with the account team (CSM, AE, SE) on risk, renewal, and expansion — but you're the technical voice in the room, not the commercial one.

What we're looking for

• 5 years in a customer-facing technical role — Solutions Architect, Customer Engineer, SRE, or Senior Support Engineer at an infra company. You've owned strategic accounts before.
• Deep cloud-native chops: Kubernetes, service mesh (Istio, Cilium), API gateways and proxies (Envoy or similar). You've debugged these in production, not just deployed them.
• 1 years hands-on with AI/ML infrastructure — LLMs, agentic frameworks, model-serving platforms, inference gateways. You don't need to have trained a model, but you should understand how production AI traffic actually flows.
• Scripting/programming comfort in Go, Python, or Bash. You'll write diagnostics, automation, and reference code.
• The ability to talk to a platform engineer at 10am and a CTO at 2pm without changing who you are.

Why this is interesting

A few honest reasons an engineer might take this seriously:

• The technical surface is genuinely new. Securing agent traffic, routing LLM calls across providers, building enterprise-grade gateways for non-deterministic systems — most of this didn't exist as a discipline two years ago. You'll be defining the patterns, not implementing someone else's.
• You'll work on production systems that matter. Our customers include some of the largest companies in the world. The architectures you design get run at real scale, under real load, by teams who care.
• Closer to engineering than most SA roles. This is a company built by infrastructure engineers, and the SA org has direct influence on what gets built. Your customer escalations become Jira tickets become shipped features.
• Remote-first, globally distributed. Laptop WFH stipend monthly phone/internet allowance. Premium-paid healthcare. Equity. Flexible hours.