Principal Software Engineer

Lead AI-native engineering practices across the team, using AI throughout the software development lifecycle to accelerate design, coding, testing, debugging, code comprehension, documentation, and operational analysis. Identify and develop new ways to use AI to solve complex engineering problems, improve developer productivity, automate repetitive engineering work, and increase the speed and quality of software delivery. Champion the responsible use of AI-generated code and engineering artifacts, ensuring appropriate human review and adherence to security, privacy, quality, and Responsible AI practices. Provide technical leadership for the Forensics Pipeline, driving architecture and engineering decisions across large-scale distributed data-processing systems spanning Substrate, Azure COSMIC, Synapse, storage, routing, transformation, and related platform components. Design and build high-scale, resilient, and cost-efficient distributed systems, considering throughput, capacity, reliability, failure isolation, disaster recovery, performance, security, privacy, and COGS. Work extensively within the Substrate codebase, understanding complex dependencies and safely introducing changes into mature, business-critical infrastructure. Develop and operate large-scale data-processing solutions using Azure COSMIC and Synapse, including transformation, orchestration, storage, capacity management, deployment, and operational troubleshooting. Establish end-to-end observability and measurable engineering outcomes, using telemetry to understand reliability, latency, capacity, operational health, and production behavior. Diagnose difficult production problems using telemetry and code and data analysis; lead root-cause investigations and ensure learnings translate into durable engineering improvements. Collaborate across Substrate, Azure, security, and partner teams, driving technical alignment and resolving complex cross-team dependencies. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Demonstrated AI-native software engineering experience, with substantial use of generative AI across coding, design, testing, debugging, code comprehension, documentation, analysis, or developer-productivity workflows. Proven ability to identify and apply AI to engineering problems, going beyond basic code completion to materially improve engineering velocity, quality, automation, or problem solving. Solid understanding of the responsible application of AI in software engineering, including human accountability for AI-generated code and artifacts, validation, security, privacy, and appropriate engineering controls. These expectations align with the Role Library's emphasis on disciplined AI use throughout the SDLC and Responsible AI practices. Experience with cloud-scale data processing, including distributed processing, data pipelines, storage systems, streaming or event-driven architectures, and high-volume telemetry. Experience developing and operating production services, including telemetry, monitoring, incident investigation, debugging, deployment, live-site response, and root-cause analysis. Experience leading design and code reviews and raising engineering quality through technical guidance and mentoring.