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Tier-1 brand plus metro location and popular cloud/AI domain create moderate competition.
Requires deep cloud, MLOps, and platform engineering experience, limiting cross-industry transferability.
Explicit 12+ years and 5+ years architecture plus specific cloud/ML requirements make filters strict.
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Lead architecture, engineering, and operational excellence of cloud-native, data-intensive AI/ML enterprise applications.
Own end-to-end architecture, technical roadmap, platform scalability, reliability, and engineering practices including MLOps/LLMOps.
Provide hands-on technical leadership, mentor engineers, manage technical governance, and partner across Product, Security, Infrastructure, and Data Science teams.
12+ years of software engineering experience.
5+ years in architecture or technical leadership roles.
Expertise in programming (Java, Python, or Go), frameworks (ReactJS, Angular, NodeJS), and strong experience with OOAD, microservices, distributed systems, API design, and databases (PostgreSQL, SQL Server, Oracle, NoSQL).
Strong understanding and hands-on experience in AI/ML fundamentals, model lifecycle, deployment patterns, and expertise with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), including Generative AI use cases and MLOps/LLMOps practices.
Experienced leader with a proven track record designing and operationalizing scalable, secure, cloud-native AI/ML solutions in enterprise environments.
Demonstrates strategic technical leadership in architecture, governance, and adoption of advanced AI/ML practices including Generative AI and responsible AI.
Strong cross-functional collaborator capable of communicating architecture and design decisions to business and executive stakeholders effectively.