AI Platform Engineer

OnePay

33d•$150,000 - $190,000•Remote

About The Position

As a Platform Engineer (AI & Automation) at OnePay, you are the technical force responsible for transforming AI strategy into production reality. You will embed within cross-functional teams to design, build, and deploy the agentic systems and intelligent tooling that automate complex workflows and 10X their impact.

Requirements

5+ years of professional engineering experience shipping production code to write clean, maintainable, and well-tested code.
Hands-on expertise with modern AI tooling, including LLM APIs, agent frameworks (LangGraph, Claude SDK), developer tools (Cursor/Claude Code), MCP server development, and familiarity with LLM evaluation techniques (prompt regression testing, human-in-the-loop review, and automated eval pipelines).
Systems integration experience, including a working knowledge of REST APIs, data pipelines (SQL), and cloud infrastructure (GCP/AWS).
A "Product Mindset"—proactively finding friction points, designing solutions, and presenting trade-offs to all audiences—along with the drive and proactivity to "walk across org lines" to get things done.

Nice To Haves

Familiarity with modern software engineering practices will help you ramp up quickly.

Responsibilities

Operate as an AI-native engineer, utilizing tools like Cursor and Claude Code to rapidly prototype, deploy, and ship production-grade AI agents and automation workflows that solve high-stakes business problems in cross-functional organizations.
Lead structured discovery sessions with business stakeholders and Subject Matter Experts to surface requirements, assess feasibility, and translate manual processes into clear, performant technical specifications and agentic architectures.
Build, maintain, and secure robust integrations between the core SaaS stack and custom AI services, instrumenting monitoring, guardrails, and evaluation frameworks to ensure all AI-driven workflows are accurate, compliant (including PII handling and audit logging), and resilient at scale.
Act as a technical force multiplier by empowering and educating internal partners to adopt AI-first mindsets, and create reusable playbooks, architecture decision records, and handoff documentation to enable teams to maintain and extend what you build.