Engineering Manager – AI

DEUNA

. Lead the AI/ML engineering team building payment-routing optimization, authorization-rate improvement, and AI-powered digital workforce systems .

Posted 9/28/2026full-timeRemote • California • United StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading AI/ML engineering teams, focusing on payment-routing optimization and backend system development. Proficient in managing team performance, guiding technical architecture, and ensuring high standards in code quality and infrastructure.

Highest-signal resume keywords

AI/ML Engineering LeadershipBackend System DevelopmentTeam Management and DevelopmentAWS Infrastructure ManagementPCI-DSS Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringMachine Learning SystemsModel Training and ServingGo ProgrammingPython ProgrammingGRPCREST APIsEvent StreamingDistributed SystemsLLM Tooling

Soft Skills

Clear CommunicationProactive CollaborationCoaching and Mentoring

Tools & Technologies

AWSTerraformObservability ToolsVector DatabasesPayment Integrations

Industry Keywords

FintechPaymentsRegulated DomainLatency-Sensitive SystemsPCI-DSS

Tech Stack

Tools & technologies

AWSDistributed SystemsGRPCPythonTerraformGo

About the role

Key responsibilities & impact

Lead the AI/ML engineering team building payment-routing optimization, authorization-rate improvement, and AI-powered digital workforce systems
Manage approximately 7–8 ML, backend, and platform engineers
Guide architecture decisions and unblock the team while remaining technically engaged
Own team delivery, including scoping, costing, and sequencing initiatives
Hire, develop, and retain engineers; manage performance and career growth
Coach engineers through technical designs, code reviews, architecture reviews, and trade-offs
Set standards for code quality, testing, and CI/CD
Guide ML model lifecycle architecture, including training, evaluation, monitoring, and retraining
Guide LLM workflows, agent orchestration, RAG pipelines, and vector database integrations
Oversee inference services for live payment routing and ensure latency and reliability
Ensure AWS infrastructure, CI/CD, observability, dashboards, tracing, and on-call runbooks meet high standards
Apply PCI-DSS and data-handling judgment to payment-data systems
Translate product vision into a technical roadmap
Collaborate with product, operations, and modeling leadership
Report team progress and blockers to leadership

Requirements

What you’ll need

8+ years in software engineering
2-3+ years in a people management role leading engineers
Significant experience building and shipping backend and/or ML systems at scale
Ideally, exposure to fintech, payments, or another regulated, latency-sensitive domain
Experience hiring, developing, and retaining an engineering team
Hands-on familiarity with modern AI/ML systems, including model training and serving, LLM-powered workflows, agents, RAG, and orchestration
Practical exposure to LLM-based systems in production
Clear and proactive communication with teams and cross-functional partners
Comfortable working in a fast-moving startup environment
Experience with Go, Python, gRPC, REST APIs, event streaming, distributed systems, AWS, Terraform, ML frameworks, LLM tooling, vector databases, PCI-DSS, observability tools, and payment integrations

Benefits

Comp & perks

Vacations and additional PTO
Remote work from anywhere
Economic support for health insurance, internet and cell phone line
Stock options
Learning and development platform
Multidisciplinary, diverse and dynamic team
Growth and career path