About the RoleDEUNA 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 DoML & 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 (
- 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 SkillsBackend / 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.
