Principal Software Engineer, AI Content Systems

Building on this foundation, you will guide the integration of LLM-powered capabilities into production systems—defining patterns for retrieval, orchestration, evaluation, and responsible AI. Architect and evolve backend services, APIs, data infrastructure, and platform capabilities that operate at global scale. Ensure systems meet stringent requirements for availability, latency, throughput, security, privacy, and cost efficiency. Establish patterns for retrieval, grounding, orchestration, memory, and tool use in production systems. Ensure responsible AI practices, including safety, privacy, and governance, are embedded into system design. Define and drive long-term technical strategy for large-scale distributed systems and platforms spanning multiple teams and organizations. Establish architectural principles, patterns, and standards that ensure consistency, scalability, and maintainability across services. Lead the design of system-of-systems architectures, integrating services, data, and AI capabilities into cohesive platforms. Make high-impact technical decisions that balance innovation, risk, cost, and long-term sustainability. Bachelor'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 Master'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 Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Prior experience with Search, Recommendation, Retrieval or ML Systems highly preferred Proven track record of architecting and delivering large-scale distributed systems or platforms used by millions of users. Deep expertise in backend systems, cloud-native architecture, and service-oriented or microservices-based design. Experience owning and evolving production systems with high availability, low latency, and solid operational rigor. Solid fundamentals in system design, distributed systems, data modeling, and performance optimization. Demonstrated ability to drive technical strategy and influence across multiple teams or organizations. Experience leading complex, ambiguous, and high-impact technical initiatives end-to-end. Experience designing and scaling LLM-powered applications, AI agents, or intelligent platforms in production. Deep expertise in prompt orchestration, retrieval systems, agent workflows, and tool integration. Experience building evaluation and experimentation frameworks for AI systems (quality, safety, latency, business impact). Proven ability to integrate AI capabilities into large-scale platforms in a reliable, secure, and cost-efficient manner. Experience with responsible AI practices, governance, and safety systems. Track record of defining industry-leading technical approaches or influencing platform-level direction.