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Tier-1 brand, metro location, and broad full-stack plus AI skillset increase candidate density.
Specialized applied AI leadership and enterprise architecture needs make cross-industry transferability limited.
Multiple explicit years requirements (10+,7+,5+,2+) plus specific tech, architecture, and leadership mandates.
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Set vision and drive engineering strategy for enterprise Applied AI solutions, integrating GenAI and agentic capabilities into products.
Own architecture, design, standards, and reference architectures; stay hands-on with code and technical delivery across teams.
Lead and mentor engineers and emerging leaders; influence organization-wide Applied AI engineering practices and foster innovation.
Bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline.
10+ years full-stack software engineering experience with technologies like Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, REST/SOAP/GraphQL, PyTorch, TensorFlow, LangChain.
7+ years architecting enterprise solutions on cloud hyperscalers (Azure, AWS, GCP) including AI/ML services and cloud-native engineering.
5+ years building AI/ML and agentic applications with hands-on GenAI experience in LLM integration, RAG pipelines, prompt engineering, vector databases, AI agent orchestration.
Experienced engineering leader with deep expertise in Applied AI and enterprise software architecture driving large-scale, outcome-focused product delivery.
Demonstrates a hands-on leadership style, balancing strategic direction with active technical contribution and team mentorship.
Strong track record of implementing modern engineering standards, DevSecOps, and cost-aware cloud-native AI solutions aligned with business strategy.