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Tier-1 employer, metro location, and broad AI leadership requirements create high competition.
High because role demands deep ML/GenAI platform expertise, model governance, and regulated healthcare experience.
High due to explicit 15+ years requirement plus mandatory ML/GenAI, cloud, and regulated-environment expertise.
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Define and lead multi-year technical vision and architecture for enterprise-scale AI applications and platforms, ensuring security, reliability, scalability, and cost efficiency.
Provide technical leadership across multiple AI initiatives, including reviewing designs, driving shared components (APIs, model registries, developer tools), and embedding responsible AI principles (bias testing, governance, security).
Collaborate cross-functionally with Product, Data Science, Security, and Compliance to translate strategy into roadmaps, influence technical adoption, and mentor senior engineers and technical leads.
15+ years of experience in software/AI engineering with strong technical leadership and influencing skills.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience); advanced degree preferred.
Deep expertise in distributed, cloud-native systems, microservices, ML/GenAI solution patterns, model lifecycle management, and ML Ops.
Proficiency with Python, JavaScript/TypeScript, front-end and back-end frameworks, CI/CD, infrastructure-as-code, containerization (Docker/Kubernetes), and cloud platforms (AWS, Azure, GCP) for secure AI/ML deployments.
Experienced in leading technical strategy and architecture for AI at enterprise scale, balancing innovation with operational governance and cost efficiency.
Skilled in cross-organizational influence without direct line authority, capable of guiding multiple teams and driving adoption of AI standards and reusable components.
Strong background in responsible AI practices, embedding security, privacy, and ethical considerations into AI delivery within regulated environments.