This role is ideal for an experienced engineering leader who is passionate about technology, thrives in high-growth environments, enjoys solving complex technical challenges, and is eager to drive technological innovation.
What Youll Do:
Responsibilities:
Lead and manage the platform/DevOps engineering team, including hiring, mentorship, performance reviews, and goal-setting.
Own the design and architecture of core infrastructure and platform services supporting all products.
Ensure scalability, reliability, and high performance of production systems.
Drive Infrastructure as Code and GitOps practices across cloud environments.
Design and operate large-scale cloud services (AWS/Azure/GCP), including cost and security ownership.
Implement and continuously improve DevOps practices, CI/CD pipelines, and observability (monitoring, logging, alerting).
Make technical decisions on large-scale data technologies such as Kafka, Spark, and OpenSearch.
Work within Agile methodologies and collaborate closely with product, R&D, and other engineering teams.
Own cross-product platform capabilities, ensuring consistency and engineering standards across teams.
Champion a culture of automation, engineering efficiency, and continuous improvement suited to a high-growth startup.
Manage the team's priorities, roadmap, and technical budget in coordination with engineering leadership.
2+ years of experience managing engineering teams.
10+ years of professional experience in the software industry.
Strong hands-on experience with modern programming languages such as Python, TypeScript, or Go.
Strong understanding of software engineering principles, including SOLID, infrastructure architecture, Infrastructure as Code, and GitOps.
Experience designing and operating large-scale cloud services on AWS, Azure, or GCP.
Strong proficiency in DevOps practices, observability, and operating production cloud-based systems.
Hands-on experience working in Agile environments and building CI/CD pipelines.
Experience in high-growth startup environments, with a strong mindset around scalability, automation, and engineering efficiency.
Familiarity with large-scale data technologies such as Kafka, Spark, and OpenSearch.
