About DEUNA

DEUNA is a payments infrastructure platform that helps enterprise merchants across Latin America, the US, and Europe optimize and orchestrate their entire payment stack. We combine payment routing intelligence, AI-driven optimization, and a composable checkout experience to help companies increase revenue and reduce operational complexity at scale. We are backed by leading investors and processing billions of dollars in annual transaction volume.

About the Role

DEUNA is a payments infrastructure company powering enterprise commerce across Latin America, the US, and Europe. We operate at the intersection of high-volume payment orchestration and applied AI — building intelligent systems that optimize authorization rates, reduce costs, and automate complex payment workflows for some of the largest merchants in the world.

We are looking for a Staff/Principal-level AI Platform Tech Lead to own the full technical stack behind our AI payment intelligence and digital workforce products — from ML model training through production routing integration. This is a hands-on leadership role: you will set the architecture, write the code, and grow the team.

What You Will Do

ML & AI Systems

Design, train, and own the full lifecycle of ML models for payment optimization — routing decisions, authorization rate improvement, cost reduction, and fraud signals — using PyTorch, TensorFlow, or XGBoost.

Build and operate LLM-powered workflows: LangGraph agent orchestration, RAG pipelines, and vector DB integrations (Pinecone, pgvector, or Weaviate).

Own the MLOps stack end-to-end: experiment tracking (MLflow / W&B), model registry, feature store, and automated retraining pipelines on AWS SageMaker.

Monitor model health continuously — drift, distribution shifts, retraining triggers — and define evaluation metrics tied directly to business outcomes.

Platform Engineering & Payments Integration

Build and maintain inference services in Go and Python integrated into live payment routing — strict latency SLAs (<100 ms), zero silent errors.

Own AWS infrastructure: ECS/EKS, Terraform IaC, SQS/SNS event streaming, RDS/Aurora, and S3 for model artifacts.

Design and ship on-premise and hybrid deployment architectures for enterprise clients requiring local data residency, including secure data sync pipelines.

Apply PCI-DSS standards across all components touching payment data; implement tokenization in ML pipelines; design for PSP-specific behavior (Cybersource, Worldpay, Prosa, Cielo, Pagbank, and others).

Build and maintain RESTful and gRPC APIs that expose AI platform capabilities to merchants and partners.

Technical Leadership

Own observability end-to-end: Prometheus/Grafana dashboards, OpenTelemetry tracing, model-specific monitors, and on-call runbooks.

Set the engineering bar for the team: architecture reviews, code standards, testing strategy (unit, integration, shadow mode), and CI/CD practices.

Mentor engineers, run design reviews, and translate product vision into executable technical roadmaps with clear timelines and trade-offs.

Technical Skills

Backend / Platform

Go (production services)

Python (ML + tooling)

gRPC & REST APIs

Event streaming (SQS/SNS)

Distributed systems

Cloud & Infra — AWS

ECS / EKS

Terraform / IaC

SageMaker or Vertex AI

RDS/Aurora, S3

Hybrid / on-prem deploy

AI / ML Stack

PyTorch or TensorFlow

XGBoost / scikit-learn

MLflow / W&B

Feature stores

Model monitoring & drift

LLMs & Agents

LangGraph / LangChain

RAG + vector DBs

Prompt engineering

LLM evaluation

Structured outputs

Payments Domain

PCI-DSS compliance

Tokenization patterns

PSP integrations

Auth rate optimization

Routing orchestration

Frontend

React / Next.js

TypeScript

Component systems

API integration

Observability

Prometheus / Grafana

OpenTelemetry

Structured logging

On-call runbooks

Data

SQL (analytical)

Airflow / dbt

Feature pipelines

Data quality & lineage

What We Are Looking For

8+ years in software engineering; 3+ at Staff, Principal, or Tech Lead level owning a production platform end-to-end.

Proven track record shipping ML/AI systems to production: training, serving, monitoring, and retraining — not just prototyping.

Hands-on LLM experience in production: agents, RAG pipelines, or AI workflow orchestration.

Payments or fintech background with practical knowledge of PSP behavior, PCI-DSS scope, authorization logic, and routing trade-offs.

Experience designing and deploying on-premise or hybrid enterprise infrastructure.

Bachelor's degree in Computer Science, Engineering, or equivalent demonstrated depth.

What we offer

A greenfield opportunity to define architecture, tooling, and engineering standards for an AI platform operating at scale across LatAm, US, and Europe.

Ownership of one of the most technically complex and business-critical systems at DEUNA — from model training through live payment routing.
Direct collaboration with product, operations, and modeling leadership — short feedback loops, high autonomy, real impact.

Competitive compensation, hybrid work and a team that takes engineering craft seriously.