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AI Platform Tech Lead

DeunaSan Francisco, US

LeadFull time
Source-verified: read directly from this employer's own lever job board, not a repost.HybridPosted (5 months ago)Last verified (today)

At a glance

Location
San Francisco, US
Workplace
Hybrid
Pay
Not published by the employer
Employment type
Full time
Experience
Not stated
Education
Bachelor (or equivalent)
Job family
Not classified
Seniority
Lead
Posted by employer
22 May 2026
Last verified open
23 October 2026
Region and country
US
Listed via
Lever

What the employer wrote

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.

Where this record came from

Read from Deuna's own Lever job board on , and last confirmed still open on . The employer published it on 22 May 2026. Jobsearch.ing did not write, edit or rank this posting, and does not vet the employer. View the original posting.

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