Lead Software Engineer - Go / Kubernetes / Python - Public Cloud Engineering

Overview

Lead the design and delivery of trusted identity services for a secure, scalable public cloud platform. You will shape architectural direction and drive engineering excellence across identity and platform infrastructure in a collaborative, cross-team environment. This role combines hands-on delivery with coaching to raise operational stability and developer experience. You’ll join at the ground level to help build a new IAM team that supports global engineering partners and growth.

Pay / Benefits

• comprehensive health care coverage
• on-site health and wellness centers
• retirement savings plan
• backup childcare
• tuition reimbursement
• mental health support

• Design and implement platform services with focus on architecture, integration, and reliability
• Develop and review secure production code and ensure quality across origins
• Identify automation opportunities to improve operational stability
• Lead design reviews and architecture discussions to enable scalable delivery
• Align designs with platform architecture and IAM consumers across teams
• Lead communities of practice to promote new technologies
• Mentor engineers through hands-on coaching
• Foster a culture of inclusion, continuous improvement, and shared learning

• Formal training or certification in software engineering concepts and applied experience
• Hands-on experience in system design, development, testing, and operational stability
• Experience with Identity and Access Management platforms, RBAC, or entitlement governance at scale
• Proficiency in Java, Spring, Go, Python, Terraform, or Kubernetes
• Cloud-native experience with at least one public cloud provider (AWS, Azure, GCP)
• Proficiency in automation and continuous delivery methods
• Understanding of agile practices including CI/CD, resiliency, and security
• Ability to connect engineering decisions to user and business outcomes
• Strong communication tailored to technical and non-technical audiences
• Responsible use of approved AI tooling with quality and security considerations

• collaboration
• coaching/mentoring
• effective communication
• Identity and Access Management (IAM)
• RBAC/entitlement governance
• Cloud-native development