Staff Software Engineer, DataRobot

• 7+ years of backend engineering experience building scalable, high-performance distributed systems / services
• Strong experience with performance optimization: e.g. profiling, latency tuning, concurrency, caching strategies
• Deep experience with autoscaling, resource management, load balancing, throughput/latency SLAs
• Solid programming skills in one or more backend languages (e.g. Python, Java, Go, C++, or equivalent)
• Strong understanding of observability and monitoring: metrics, tracing, logging; and instrumentation of services
• Design and architect scalable AI-backed services and applications, integrating AI models into production systems with high performance, reliability, and low latency
• Ability to solve ambiguous challenges and influence technical direction across teams, balancing performance, accuracy, and cost
• Experience operating across multiple cloud providers (AWS, GCP, Azure) and/or hybrid environments

Desirable

• As a Staff Software Engineer focused on Application Scalability & Performance, you will lead the design, implementation, and operation of backend systems that power high-throughput AI applications
• Your work will ensure our applications perform with high accuracy, minimal latency, and robust scalability (including autoscaling), all while maintaining reliability, cost-effectiveness, and maintainability
• You will collaborate closely with Product, Platform, and AL/ML teams to deliver high impact
• Architect, build, and lead backend services that scale to handle large workloads, high concurrency, and low latency requirements
• Design and implement autoscaling strategies (horizontal/vertical), dynamic resource allocation, and load balancing to ensure responsive, cost-efficient service
• Improve end-to-end request pipelines, optimizing for latency, throughput, reliability, and correctness
• Instrument, monitor, and profile systems in production; identify bottlenecks, troubleshoot performance issues, and proactively tune services
• Collaborate with ML/AI teams to ensure models’ serving pipelines uphold accuracy, consistency, and performance under load
• Drive best practices in systems reliability, observability, error handling, capacity planning, resilience, and failover
• Mentor and coach other engineers; provide technical leadership and influence across teams
• Contribute to defining architecture, coding standards, performance benchmarks, and technical roadmap items related to scalability and performance