Pareto Agent - VC-backed AI startup building a policy-driven runtime for high-stakes commercial workflows.
Join Pareto Agent as the first engineering hire to build the execution layer for autonomous B2B sales agents. Unlike standard LLM wrappers, you will architect a deterministic, policy-driven runtime that governs agent actions in real-world negotiations. Reporting to a serial-entrepreneur CTO, you'll ensure every AI decision protects revenue and follows strict guardrails.
Location: San Francisco, USA
Why This Role Is Remarkable
Founding opportunity as the first engineer, offering significant 1.5% equity and direct influence on the technical architecture of a $3.5M-funded startup.
Work alongside serial founders Evan Liang (ex-LeanData CEO) and Maurizio Greco (20+ year CTO) who have successfully scaled multiple B2B companies.
Tackle deep systems engineering challenges by moving beyond simple chat interfaces to build a self-improving, safe-by-construction execution system for high-stakes commerce.
What You Will Do
Design and own the multi-stage agent pipeline, including intent classification, context assembly, and reasoning loops to enable reliable autonomous decision-making.
Build a robust event-driven runtime and evaluation framework to enforce commercial policies and catch regressions before they impact customers.
Architect sophisticated context management systems that determine how to retrieve, compress, and utilize data as agent complexity scales across various industries.
The Ideal Candidate
Proven experience building production-grade LLM systems where reliability was mission-critical, moving beyond "it usually works" to deterministic outcomes.
Strong systems thinking with professional proficiency in typed languages such as TypeScript, Go, or Rust for building scalable, type-safe infrastructure.
Self-directed engineer comfortable in early-stage environments who can diagnose whether failures stem from prompts, system design, or LLM limitations.