Lead Software Engineer – Cloud

Overview

As a Lead Software Engineer in the Container Platforms group, you design and evolve Kubernetes-based platform capabilities that empower engineers to deploy, run, and scale services securely. You will collaborate with security, identity, and platform teams to deliver a best-in-class developer experience at scale. This hands-on role focuses on reliability, operational maturity, and shaping engineering culture across the firm. You will drive secure-by-default patterns and contribute to technical direction and standards.

Responsibilities

• Design, build, and maintain Kubernetes platform components (cluster services, controllers, operators, admission policies, APIs, developer tooling)
• Develop backend services and automation in Go and Python to improve reliability and self-service for engineers
• Create delivery workflows to standardize practices and reduce toil across the platform
• Enhance observability and readiness (monitoring, logging, tracing, alerting, runbooks, on-call)
• Collaborate with security and risk teams to implement secure-by-default patterns (identity, policy, network controls, secrets)
• Contribute to technical direction via design docs, architecture reviews, and engineering standards
• Mentor engineers through code reviews, pairing, and mob programming
• Promote enterprise AI-assisted engineering practices to improve quality, speed, and reliability with validated outputs
• Leverage SDLC tools and AI-assisted development and automation capabilities to maximize automation value

Key requirements

• Formal training or certification on software engineering concepts and advanced applied experience
• Strong Kubernetes experience (workloads, services, networking, storage, RBAC, upgrades, operations, troubleshooting)
• Cloud development experience designing distributed systems and scaling in cloud environments
• Proficiency in Go and Python for building platform services and tooling
• Collaborative team experience including pair or mob programming
• Solid fundamentals in data structures, networking, Linux, containers, and secure coding
• Hands-on experience with enterprise AI-assisted development tools and ability to evaluate AI outputs for correctness, performance, and security
• Understanding of responsible AI use and security considerations in engineering workflows

• Collaborative
• Agile/mob programming oriented
• Strong communication and iterative delivery
• Kubernetes (clusters, scheduling, RBAC, upgrades)
• Go
• Python

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