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Tier-1 brand and Bangalore metro increase competition, but very senior specialized role moderates applicant density.
Deep regulated healthcare AI and governance requirements reduce cross-industry transferability.
Mandatory 15+ years, deep ML/AI platform expertise, and regulatory controls increase filter rigidity.
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Lead the technical vision and architecture for enterprise-scale AI applications and platforms, focusing on Generative AI and machine learning solutions.
Establish and enforce architecture standards including security, reliability, scalability, and operational performance for AI products powering healthcare outcomes.
Provide technical leadership across AI initiatives by reviewing designs, driving shared platform components, embedding responsible AI practices, and collaborating cross-functionally without direct authority.
15+ years in software or AI engineering with demonstrated technical leadership and influence over senior engineers and managers.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field; advanced degree preferred.
Strong expertise in cloud-native distributed systems, microservices, AI/ML lifecycle management, and multi-cloud AI deployments (AWS, Azure, or GCP).
Proficiency in Python and JavaScript/TypeScript stacks, experience with CI/CD, Docker/Kubernetes, modern ML infrastructure, and embedding security and privacy practices.
Experienced leader in building and scaling AI platforms and model governance frameworks in regulated or enterprise environments.
Strategic thinker capable of aligning technical roadmaps with business outcomes and influencing cross-functional teams through expertise rather than authority.
Hands-on with state-of-the-art AI technologies including generative models, retrieval augmented generation, vector DBs, and practical machine learning operations.