Software Engineer - Agent Architecture

Staff Software Engineer - Agent Architecture

Remote

At Pay Near Me , we’re on a mission to make paying and getting paid as simple as possible. We build innovative technology that transforms the way businesses and their customers experience payments. Our industry‑leading platform, PayXM™, is the first of its kind—designed to manage the entire payment experience from start to finish. Every click, swipe or tap is seamless, fast and secure, helping non‑commerce businesses boost customer satisfaction, accelerate payments, and reduce costs.

Our single platform handles it all: cards, ACH, digital wallets such as Pay Pal, Venmo, Cash App Pay, Apple Pay and Google Pay, and even cash at more than 62,000 retail locations nationwide. Today, thousands of businesses across consumer lending, iGaming and online sports betting, property management, and tolling trust Pay Near Me  to deliver a payment experience that drives real results.

We’re a team of 300+ employees across 41 states, headquartered in Silicon Valley with satellite offices in Dallas, TX and Holmdel, NJ.

We build agentic AI products that our customers interact with across different modalities. These agents sit on top of the same money‑movement platform that handles real funds for businesses in regulated industries, so they have to be safe, compliant, and predictable in ways most consumer AI products are not.

We’re looking for a Staff Engineer to own the architecture and implementation of these agents end‑to‑end. This is a builder role for someone who has shipped agents to production at scale, not just used them. You will define how we build agents at Pay Near Me : the frameworks, the integration patterns with our existing systems, the guardrails around money and PII, and the testing/eval/observability loop that lets us improve agents safely over time.

Our core platform stack is Ruby on Rails with MySQL (monolith) plus Go microservices on AWS/Kubernetes, with Datadog for observability. Our agents interact with consumers and business partners across a wide variety of use cases.

• Own the architectural direction for agentic AI at Pay Near Me  in partnership with other engineering leaders. We are building an agent platform, not a single agent—our business customers have different rules, brand voices, allowed actions, knowledge bases, and compliance postures, and the architecture has to treat per‑tenant configuration, isolation, and evaluation as first‑class concerns. Produce and maintain architecture documentation (current state, target state, migration plan) and drive alignment across product, engineering, security, and compliance.
• Design, build, and ship production agents—including voice and chat agents for a wide range of payment‑related activities—that integrate cleanly with our Ruby on Rails / MySQL platform and partner services (Eleven Labs, Twilio, and others). Treat tool design as a first‑class discipline: tool schemas, descriptions, idempotency, side‑effect semantics, and error surfaces directly determine agent quality, and for money‑moving tools they determine whether we can stand behind every action the agent took.
• Make and defend the "what kind of intelligence goes where" decisions: when to lean on a partner's stack vs. orchestrate frontier LLMs directly, when RAG is the right answer vs. tool calls vs. fine‑tuning, when a small/fast/cheap model is sufficient vs. when a frontier model is warranted, and where classical ML or deterministic logic is a better fit than an LLM ign the seams that let us swap providers, voice vendors, and models as the landscape shifts—without rewriting the agents that sit on top of them.
• Design and operate the agent lifecycle as a closed loop: testing, offline evals, online evals, observability, scoring, and a disciplined feedback path from what we observe in production back into the test suite and eval set. Own the rollout discipline for non‑deterministic systems: prompt and agent versioning, shadow mode, canary‑by‑tenant, gradual ramps, and rollback playbooks that account for the fact that the "bad version" may have already taken real payments.
  
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