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Design and develop scalable AI-powered backend systems for SysML-based engineering environments
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Build and maintain distributed data ingestion and ETL pipelines for large-scale engineering artifacts and technical documentation
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Develop and optimize LLM-powered workflows for metadata extraction, semantic analysis, and entity resolution
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Implement AI agents and multi-agent orchestration workflows
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Design and improve RAG-based architectures and semantic retrieval pipelines
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Develop graph-based knowledge representation and traceability analysis solutions
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Work with graph databases, graph processing libraries, and semantic relationship modeling
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Build and optimize distributed data processing workflows using Apache Spark
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Collaborate with cross-functional engineering teams to integrate AI capabilities into platform services
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Design scalable and high-performance APIs and backend services
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Improve system reliability, scalability, observability, and performance across distributed environments
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Participate in architecture discussions and technical decision-making processes
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Contribute to cloud-native infrastructure and deployment workflows
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Support deployments in secure, air-gapped, or classified environments when required
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Create and maintain technical documentation and engineering best practices