Responsibilities include making architectural decisions spanning distributed systems, AI orchestration, identity, privacy, compliance, reliability, and multi-tenant design; writing and reviewing production code; establishing engineering and operational standards; and guiding solutions from design through operation. Lead the design and development of large-scale, self-service AI, agentic, and data-platform capabilities and frameworks, including data and LLM orchestration, skills, tools, memory, retrieval, evaluation, observability, and governance. Advance AI-native software development through coding agents, agentic workflows, and harness engineering. 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. Experience with AI-native software development, including using agent harnesses such as GitHub Copilot CLI and coding agents, orchestrating multi-step agentic workflows across the software development lifecycle, and reviewing agent-generated code and pull requests with production-grade rigor. Extensive experience architecting, developing, and operating reliable, large-scale, globally distributed production systems, particularly data infrastructure. Hands-on experience with one or more of the following technologies: Airflow, Spark, Flink, Kafka, Azure Data Factory, Kubernetes, or Event Hubs. Experience designing and delivering generative AI solutions, including RAG, LLM orchestration, agentic workflows, AI evaluation and monitoring, or quality measurement. Demonstrated ability to influence without authority, align teams, and build effective partnerships with engineers, product managers, and leaders. Demonstrated technical leadership, problem-solving, and communication skills, including the ability to communicate effectively in spoken and written English. Solid understanding of data privacy, compliance, and security in large-scale distributed systems.
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