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Senior, specialized role at a strong global employer in a metro reduces mass competition but attracts experienced applicants.
Deep production AI and regulated-pharma experience matters, but core ML engineering skills remain transferable across industries.
Explicit 12+ years, mandatory production AI experience, and enterprise/regulatory requirements create strict shortlisting filters.
Lead end-to-end delivery of AI-centric use cases from discovery, prototyping to production and continuous improvement across multiple strategic business areas.
Define and drive technical direction, architecture, engineering standards, and reusable patterns for a complex portfolio of AI products ensuring reliability, security, and observability in a regulated pharmaceutical environment.
Collaborate with product managers, domain experts, and engineers to shape AI product outcomes, including engineering intelligence layers incorporating models, tools, knowledge grounding, and human-oversight controls.
Typically 12+ years of relevant experience building AI or software products with demonstrated scope and influence.
Degree required: B.E/M.E/B.Tech/M.Tech/PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related technical discipline.
Strong programming and software engineering skills including testing, documentation, APIs, CI/CD, preferably experience with GitHub.
Experience working in regulated pharmaceutical environments applying Responsible AI, data integrity, validation, and auditability is expected.
Experienced in setting enterprise-wide AI architecture and engineering standards and coaching senior engineers without formal authority.
Proficient in working at the intersection of AI engineering, product management, and business stakeholders for complex AI products in a global healthcare enterprise.
Hands-on with modern AI application patterns, AI-assisted development tools, and cloud-native AI solutions across Azure/AWS platforms with knowledge of model/tool integrations and observability.