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engineering teams and support knowledge sharing.\nMonitor application performance and ensure adherence to project timelines and quality standards.\nLead architectural design discussions and drive decisions on technology selection, system decomposition, and integration patterns.\nDesign and implement event-driven, microservices, and serverless architectures for high-availability systems.\nChampion engineering best practices, including code reviews, testing strategies, CI/CD optimization, and technical debt management.\nEvaluate and adopt emerging technologies, frameworks, and AI-powered tools to improve team productivity and solution quality.\nCollaborate with product and business stakeholders to align technical solutions with strategic objectives.\n\nRequirements: \nProficiency in software development using languages such as JavaScript, TypeScript, Python, Java, Rust, Dart, Go, Kotlin, or C++.\n6+ years of experience with the full software development lifecycle, including embedded software development, continuous integration, automated testing, and deployment.\nStrong understanding of software architecture, platform design, and cloud engineering principles.\nAbility to translate business requirements into scalable, secure, and maintainable technical solutions.\nFamiliarity with Agile methodologies and version control systems.\nDemonstrated skills in collaboration, technical leadership, and effective communication with cross-functional teams.\nExperience designing and operating distributed systems, microservices, and cloud-native applications at scale.\nDeep knowledge of at least one cloud platform (AWS, Azure, or GCP), including compute, storage, networking, and managed AI/ML services.\nExperience with container orchestration (Kubernetes, ECS), service mesh, and infrastructure-as-code (Terraform, Pulumi).\nProven ability to mentor engineers, lead design reviews, and influence technical direction.\nStrong understanding of security engineering practices, performance optimization, and observability.\n\nPreferred Qualifications: \nExperience building applications that integrate LLM APIs, RAG pipelines, or agentic AI components.\nFamiliarity with MCP (Model Context Protocol) or tool-layer integrations for AI-driven systems.\nExperience with real-time systems, streaming architectures (Kafka, Flink, Kinesis), and event sourcing patterns.\nKnowledge of WebAssembly (WASM), edge computing, or progressive web application (PWA) patterns.\nExperience with database scaling strategies, including sharding, replication, and multi-region deployments.\nContributions to open-source projects or technical community leadership.\nFamiliarity with AI governance, responsible AI practices, and data privacy regulations (GDPR, CCPA, SOC2).\nSkills\naws, azure, gcp, golang, java, javascript, microservices, python, 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