Principal Software Engineer

Lead architecture, technical strategy, and design for large-scale business data, intelligence, AI, and cloud platform systems. Define and drive technical direction across foundational platform capabilities, intelligent services, and cross-organization initiatives. Design and evolve cloud-native distributed systems that power enterprise-grade business applications, data platforms, copilots, agents, and AI-driven experiences with a focus on scalability, reliability, performance, security, governance, compliance, and operational excellence. Lead the development of AI-native platform capabilities, including enterprise retrieval and grounding systems, semantic intelligence, process intelligence, agent orchestration, intelligent automation, and LLM-powered experiences. Drive the evolution of Dataverse as the business data and intelligence platform for the AI era, enabling customers to transform enterprise data, processes, and knowledge into actionable intelligence and business outcomes. Champion AI-native engineering practices across the organization by leveraging AI throughout the software development lifecycle, accelerating innovation, improving developer productivity, and raising engineering quality. Partner with engineering leaders, product managers, architects, researchers, data scientists, and business stakeholders to shape roadmaps, influence investments, and deliver platform capabilities that unlock customer and business value. Evaluate architectural tradeoffs across data platforms, intelligence layers, AI systems, and distributed services while balancing customer needs, platform scalability, governance, cost efficiency, and long-term technical sustainability. Champion engineering excellence through secure development practices, automation, CI/CD, observability, testing, telemetry, incident management, and operational rigor for mission-critical cloud services. Mentor and develop engineers through technical leadership, architecture reviews, design coaching, AI-native engineering best practices, and leadership by example. Foster a culture of customer obsession, innovation, accountability, continuous learning, and inclusive collaboration while helping teams navigate ambiguity and deliver impact at scale. 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 These requirements include but are not limited to the following specialized security screenings: 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. Experience designing, building, and operating large-scale distributed systems, cloud platforms, data platforms, AI services, or enterprise software systems. Experience building foundational platform capabilities that serve multiple products, services, customers, or engineering organizations at scale. Deep expertise in software architecture, distributed systems, data architecture, reliability engineering, scalability, performance optimization, and operational excellence. Solid programming experience in C#, Java, Python, JavaScript, C++, or similar modern development languages. Experience with Azure, cloud-native architectures, containerized workloads, platform services, and hyperscale cloud infrastructure. Experience building or operating business data platforms, knowledge systems, enterprise data services, semantic models, metadata platforms, retrieval systems, search technologies, or intelligence platforms. Experience developing AI-powered applications, LLM-enabled experiences, retrieval and grounding systems, agent frameworks, intelligent automation solutions, production AI services, or AI-native developer experiences. Experience applying AI throughout the software development lifecycle, including AI-assisted engineering, code generation, testing, quality validation, deployment automation, and operational intelligence. Experience with modern engineering practices including CI/CD, infrastructure as code, automated testing, observability, telemetry, incident management, and DevOps. Understanding of security, privacy, governance, compliance, reliability, accessibility, and Responsible AI principles required for enterprise-scale AI systems. Ability to create clarity in ambiguous environments, influence technical direction without formal authority, and align stakeholders around long-term platform investments and architectural decisions. Solid communication skills with the ability to translate complex technical concepts into clear engineering, product, customer, and business outcomes. Demonstrated experience mentoring senior engineers, driving cross-organization technical leadership, and raising the engineering bar across large engineering teams.