Infrastructure Engineer

Founding AI Platform Engineer

Location: Boston, MA (Hybrid)

Compensation: $220K–$300K base + meaningful founding equity Stage: Pre-seed, venture-backed

About the Company:

AI agents are being deployed at massive scale, but running them is expensive. Every execution burns tokens, even when an agent is repeating work it has already done. As usage grows from thousands to millions of executions, cost grows with it.

Our client is a pre-seed AI infrastructure company building a runtime compiler that turns recurring AI agent behavior into optimized, deterministic programs. It keeps the flexibility of LLM-powered agents and adds the efficiency and reliability of traditional software. The product is a framework-agnostic middleware layer. It works with LangGraph, CrewAI and other frameworks customers already use, and it runs alongside their existing agent platform on AWS, GCP or Azure.

The Role:

You'll take the core optimization technology and make it deployable, performant and reliable inside demanding enterprise environments.

The product runs as a microservice/ sidecar next to a customer's agent stack. You'll own the architecture that makes this work across very different customer environments at scale, without adding latency or integration friction.

This is not a narrow platform role in a large organization. There's no existing codebase and no inherited tech debt. You'll shape the systems architecture from day one.

What You'll Do:

• Design and build the platform architecture that delivers the optimization engine into enterprise environments
• Package and ship the SDK and microservice/sidecar across AWS, GCP and Azure
• Build containerized, Kubernetes-native deployment infrastructure
• Engineer for performance, reliability and scale in complex customer environments
• Work closely with the founders and the AI/ML engineering lead to turn frontier research into production software
• Help set engineering standards, tooling and practices as a founding team member

What We're Looking For:

• Strong systems engineering fundamentals: distributed systems, systems design, performance engineering
• Production experience with cloud infrastructure at scale (AWS, GCP and/or Azure)
• Hands-on experience with Kubernetes and Docker
• Experience packaging and deploying software, such as SDKs, microservices or sidecars
• A record of end-to-end ownership of meaningful systems, not just narrow components
• Familiarity with agentic systems or LLM-powered applications (deep ML internals not required)
• Comfort with ambiguity and building without much existing process or infrastructure

Nice to have:

• Rust and/or Python (the core stack, but not a hard requirement; strong engineers pick up languages quickly)
• Prior startup experience
• Experience building developer tooling or infrastructure products

Why Join:

• Founding engineer seat: you'll be one of the first two engineering hires and will define the architecture
• A new problem: making large-scale agentic software economically sustainable, at the intersection of AI agents, compilers, distributed systems and cloud infrastructure
• Real ownership: end-to-end responsibility, not a narrow lane in a big organization
• Meaningful equity: the founders see early engineers as partners in the upside
• Location flexibility over time: Boston-based today, and the team won't lose an exceptional engineer over geography