AI/ML Engineering Manager - Payments Platform

DEUNA; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

DEUNA is seeking an Engineering Manager to lead our AI/ML engineering team responsible for the intelligent systems behind payment routing optimization and AI-powered digital workforce products. You will mentor engineers, influence architectural decisions, and align the team with product and leadership goals.

This hands-on management role requires depth in ML systems and backend services, with the ability to guide complex technical discussions and drive delivery at scale.

Qualifications

• 8+ years in software engineering, including 2-3+ years in a people management role leading engineers.
• Experience building and shipping backend and/or ML systems at scale, ideally with exposure to fintech, payments, or another regulated, latency-sensitive domain.
• Hands-on familiarity with modern AI/ML systems: model training and serving, LLM-powered workflows (agents, RAG, orchestration), or similar — enough to have a real technical conversation with your team and challenge their thinking when needed.

Responsibilities

• Lead an ML/AI engineering team of 7–8 engineers and own delivery for the group — scoping, costing, sequencing initiatives.
• Guide architecture decisions, review technical approaches, and unblock engineers to maintain velocity and quality.
• Hire, develop, and retain engineering talent while balancing individual growth with delivery pressure.

Skills

People management

Backend development

ML systems

Tools

Model training & serving

LLM workflows

Job description

DEUNA is seeking an Engineering Manager to lead our AI/ML engineering team responsible for the intelligent systems behind payment routing optimization and AI-powered digital workforce products. You will mentor engineers, influence architectural decisions, and align the team with product and leadership goals.

This hands-on management role requires depth in ML systems and backend services, with the ability to guide complex technical discussions and drive delivery at scale.