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Tier-1 brand, metro location, and popular full-stack engineering manager title increase candidate competition.
Requires deep full-stack, applied GenAI, and cloud expertise, making background moderately industry-specific.
Multiple explicit filters: 10+ years, mandatory AI/cloud experience, and extensive tech stack requirements.
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Own end-to-end delivery of high-visibility full-stack AI-powered products integrating GenAI and agentic capabilities.
Lead technical design, architecture, code quality, and cost management (inference, token, cloud) to ensure lean, scalable, and maintainable solutions.
Mentor and manage engineering teams, set engineering standards, and collaborate cross-functionally to align technical solutions with business outcomes.
Bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline.
10+ years full-stack software engineering including Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, and testing frameworks.
3+ years hands-on AI/ML development experience including GenAI, LLM integration, RAG pipelines, prompt engineering, vector databases, and AI agent orchestration.
3+ years cloud-native engineering experience with Azure, AWS, or GCP including AI/ML cloud services and FinOps cost-aware engineering.
Experienced leader with proven ability to manage technical architecture, engineering standards, and mentor teams in fast-paced product environments.
Strong full-stack AI engineering background with practical expertise integrating cutting-edge GenAI models and agentic AI into scalable products.
Operates with focus on delivering measurable business outcomes, cost accountability, and rapid experimentation-driven solutioning.