You will embed with engineering teams responsible for complex, large-scale services and become a technical partner in understanding how their systems consume infrastructure.
The role requires the ability to navigate complex application ecosystems, understand dependencies and architectural characteristics, and connect application and business-level workload signals to underlying compute, memory, storage, network, and platform resource consumption.
You will work with teams to establish meaningful demand models, improve observability into resource utilization, forecast future infrastructure requirements, and identify opportunities to improve efficiency.
You will also help develop common methodologies, tooling, and standards that allow these practices to scale across multiple organizations and services.
Successful candidates will combine strong systems engineering skills with curiosity, analytical thinking, and the ability to build trusted technical relationships across application, infrastructure, operations, finance, and leadership teams.
Minimum Qualifications
5+ years of software engineering experience developing, operating, or architecting large-scale distributed services and infrastructure
Strong software engineering skills and proficiency in one or more programming languages such as Java, Python, or Go, with experience designing and implementing production-quality systems, tooling, and automation
Ability to understand and reason about complex application architectures spanning multiple technologies, services, dependencies, and infrastructure layers
Strong understanding of distributed systems and cloud infrastructure, including compute, storage, networking, data technologies, and containerized environments
Experience using observability and telemetry, including metrics, logs, and performance data, to understand system behavior, resource utilization, and operational characteristics
Ability to translate complex technical problems and system behavior into scalable engineering solutions
Excellent communication skills and demonstrated ability to build effective technical partnerships and drive solutions across engineering organizations
Bachelor’s or Master’s degree in Computer Science or equivalent experience
Preferred Qualifications
Experience with infrastructure capacity planning, demand forecasting, and resource management, including connecting application and business demand to infrastructure requirements
Experience developing scalable capacity, forecasting, optimization, or resource intelligence solutions for large-scale infrastructure environments
Experience with Kubernetes and cloud-native architectures, distributed data systems, traffic management, and large-scale service platforms
Understanding of FinOps and infrastructure business operations, including cost management, procurement, data center capacity, cloud billing, and financial planning
Experience applying GenAI, LLMs, or other emerging technologies to build intelligent automation, derive insights from complex systems, and improve engineering workflows at scale
Experience with performance and efficiency engineering across application and infrastructure layers, including identifying architectural, configuration, and operational optimization opportunities
Demonstrated ability to define technical standards and methodologies, communicate complex technical concepts, and influence technical direction across engineering and organizational boundaries