Engineering Manager, Infrastructure Automation

Airwallex1 weeks ago

Location

US - Seattle

Type

Full Time

Salary

USD 201,000 – 288,000

Level

Manager

Role

Engineering Manager

Posted

Apr 3, 2026

Full TimeManager

The role

Summary

Airwallex is seeking an experienced Engineering Manager to lead a groundbreaking Infrastructure Automation team in Seattle. This role focuses on developing AI-powered agents to automate DevOps, SRE, and database operations, leveraging cutting-edge technologies to reduce operational toil and improve system reliability across a global engineering organization.

What you'll do

Team Leadership: Build and lead the Infrastructure Automation team, hiring and developing 5 engineers (3 SWE/DevOps + 2 DBA/SWE). Establish team processes, culture, and create an environment for high-performance engineering.

AI Automation Strategy: Define and execute the technical vision for AI-powered infrastructure agents, identifying and prioritizing high-impact automation opportunities across DevOps, SRE, and DBA operations.

DevOps and SRE Automation: Lead the design and development of intelligent agents for autonomous incident response, root cause analysis, infrastructure provisioning, and change management.

Database Automation: Drive development of AI agents for database operations, including schema migration validation, query performance analysis, capacity forecasting, and self-healing replication management.

Reliability and Excellence: Ensure automation systems are production-grade, reliable, and well-monitored. Participate in on-call rotations, lead postmortems, and enforce quality standards.

Cross-Functional Collaboration: Partner with Cloud Infrastructure, SRE, DBA, Observability, and Productivity teams to identify automation targets, integrate systems, and drive adoption of AI-powered tooling.

What we look for

Technical

Cloud PlatformsExpert-level experience with AWS, GCP, or Aliyun, Kubernetes, Terraform, and infrastructure-as-code practices

Programming LanguagesProficiency in backend languages such as Python, Go, Java, or Kotlin with ability to contribute to architectural decisions

SRE PracticesDeep knowledge of incident management, observability, monitoring systems (Grafana, Prometheus, Splunk, Datadog)

AI/ML TechnologiesExperience with AI/ML technologies, LLM-based systems, and applying AI to solve infrastructure and operational challenges

Education

DegreeBachelor's degree in Computer Science, Software Engineering, or related technical field preferred

Experience

Management Experience8+ years of software engineering experience, including at least 2 years in people management of a team of 3+ engineers

Database SystemsSolid understanding of relational and NoSQL database systems, including DBA operations and performance optimization

Skills

Required skills

Infrastructure AutomationProven ability to design and implement automated infrastructure and operational systems

Team LeadershipStrong skills in hiring, mentoring, and developing high-performing engineering teams

AI IntegrationCapability to leverage AI technologies to solve complex operational challenges

Nice to have

AI Agent DevelopmentExperience building LLM-powered automation pipelines or AIOps systems

Fintech ExperienceBackground in payments or regulated industries with understanding of compliance requirements

Compensation & benefits

Salary

USD 201,000 – 288,000 (annual)

Stock options

Available

Benefits

Health Insurance

Comprehensive medical, dental, and vision coverage

Equity Compensation

Stock options in a high-growth fintech startup valued at $8 billion

Professional Development

Continuous learning opportunities, conference attendance, and skill development programs

Flexible Work

Hybrid work arrangement in Seattle with flexible working hours

Global Career Opportunities

Part of a globally distributed team with potential for international collaboration

Interview process

1
Initial Screening — Phone or video call with recruiting team to assess background and fit
2
Technical Interview — Deep-dive technical discussion on infrastructure automation, AI technologies, and leadership experience
3
Leadership Interview — Meeting with engineering leadership to evaluate management approach and strategic thinking
4
Team Interaction — Virtual or in-person meetings with potential team members to assess cultural fit
5
Final Interview — Comprehensive review with senior executives, including presentation of technical vision