Software Engineer, Infrastructure

The Software Engineer, Infrastructure will be responsible for designing, scaling, and maintaining critical infrastructure that supports large-scale data systems and AI workloads. This role requires strong engineering expertise, ownership, and the ability to solve complex reliability and performance challenges.

• Design, build, and operate cloud infrastructure supporting large-scale data processing and AI workloads.


• Manage and improve production Kubernetes environments, ensuring high availability, scalability, and operational reliability.


• Develop and optimize CI/CD pipelines to improve deployment speed, testing quality, and release confidence.


• Automate engineering workflows and improve developer experience by reducing operational friction.


• Build and enhance end-to-end testing frameworks and reliability systems.


• Strengthen observability capabilities through logging, metrics, tracing, monitoring, and alerting solutions.


• Collaborate with engineering teams on architecture decisions, infrastructure improvements, and scalability initiatives.


• Support customer-facing technical integrations by guiding deployments and resolving infrastructure challenges across different environments.


• Troubleshoot complex infrastructure issues involving networking, storage, cloud services, and runtime systems.


• Drive operational excellence through automation, reliability practices, and continuous improvement initiatives.


• Contribute to building infrastructure solutions that support advanced data platforms and enterprise AI applications.

Requirements

The ideal candidate is an experienced infrastructure or platform engineer with strong programming skills and hands-on experience building reliable cloud-based systems. This role requires technical depth, problem-solving ability, and a strong sense of ownership in a dynamic engineering environment.

• 5+ years of experience in infrastructure engineering, platform engineering, distributed systems, or a related field.


• Strong programming experience with languages such as Go, Java, Python, or similar.


• Proven experience managing production Kubernetes environments and containerized applications.


• Strong knowledge of cloud platforms including AWS, GCP, or Azure.


• Experience with Docker, cloud infrastructure, and modern deployment practices.


• Deep understanding of CI/CD systems and automation workflows.


• Proficiency with infrastructure-as-code tools such as Terraform.


• Ability to debug complex, cross-layer technical issues involving networking, storage, and runtime environments.


• Experience designing scalable, reliable, and cost-efficient systems.


• Strong communication skills and ability to collaborate effectively across engineering teams.


• Ability to thrive in a fast-paced environment with high ownership and autonomy.


• Experience with data platforms, lakehouse technologies, or large-scale analytics systems is a plus.


• Familiarity with technologies such as Spark, Trino, Iceberg, Delta, Airflow, Prometheus, Grafana, ELK, or Datadog is preferred.

Benefits

• Competitive salary package with meaningful equity opportunities and performance-based bonuses.


• Comprehensive health coverage and retirement benefits with company contribution.


• Flexible remote work environment supporting autonomy and productivity.


• Unlimited paid time off policy.


• Opportunities to contribute to research, technical publications, and industry conferences.


• Opportunity to work on large-scale infrastructure powering next-generation AI and data systems.


• Collaborative engineering culture with significant technical ownership and impact.