Software Engineer, Databases Responsibilities:

• Define and drive the long-term technical vision and architecture for large-scale systems software, including platform services, runtime environments, and low-level infrastructure components
• Architect systems-level solutions that address performance, reliability, and scalability requirements across distributed infrastructure serving billions of users
• Identify and resolve the most complex systems-level challenges spanning kernel interfaces, memory management, concurrency, inter-process communication, and distributed coordination
• Lead the design and implementation of critical platform components, establishing extensible technical foundations and coding standards that improve consistency and velocity across systems engineering teams
• Develop and operationalize testing frameworks, fault injection strategies, and verification methodologies that prevent systems regressions and improve production reliability at scale
• Define and track systems-level metrics, service level objectives, and performance guardrails that connect engineering outcomes to organization-wide priorities
• Leverage AI tooling and automation to accelerate systems development workflows, identify performance bottlenecks, and improve observability and debugging capabilities
• Partner with infrastructure, product, and platform engineering teams to translate complex systems requirements into durable technical designs, influencing roadmaps across organizational boundaries
• Drive safe and automated rollout strategies for major systems changes, including phased migrations and dependency coordination across teams
• Mentor engineers across the organization on systems design principles, performance profiling, debugging methodologies, and low-level platform internals

Minimum Qualifications:

• 8+ years of experience in systems software engineering, including design and implementation of operating system interfaces, runtime environments, distributed infrastructure, or low-level platform services
• Experience architecting and owning large-scale systems infrastructure used across multiple teams or organizations, including driving multi-year technical roadmaps
• Experience identifying and resolving complex systems-level performance, reliability, or correctness issues spanning concurrency, memory management, or distributed coordination
• Experience defining engineering standards, architectural patterns, and verification methodologies that improve systems quality and consistency at scale
• Experience communicating complex systems architecture and technical strategy in writing and presentations to both technical and non-technical stakeholders

Preferred Qualifications:

• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience leading database migrations, schema evolution, or platform modernization efforts in large-scale production environments
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with database internals, like storage engines
• Experience with distributed database systems, consensus protocols (such as Raft or Paxos), or building highly available data infrastructure
• Experience applying AI and machine learning techniques to database optimization problems, such as query optimization, workload prediction, or automated performance tuning

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