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Strong employer brand, metro location, and broad AI skill requirements increase candidate competition significantly.
Advanced ML/AI and commercial AI expertise are transferable, but pharma compliance increases domain specificity moderately.
Explicit 9+ years, deep generative AI and production MLOps requirements make shortlisting highly strict.
Lead design, development, and deployment of end-to-end AI architectures focused on commercial initiatives including data ingestion, model inference, and application layers.
Own and implement advanced Generative AI systems such as Retrieval-Augmented Generation (RAG), multi-agent orchestration frameworks, and LLM deployment strategies.
Set technical direction, mentor senior engineers, and collaborate with leadership and stakeholders to translate business goals into scalable AI technical solutions.
Bachelor’s or master’s degree in computer science, engineering, mathematics, or equivalent demonstrated expertise in AI/ML systems architecture.
9+ years of progressive, hands-on experience in software engineering, AI/ML, and data architecture with production system delivery.
Deep practitioner-level expertise in Generative AI including LLM integration, prompt engineering, fine-tuning, and managing output guardrails.
Work Location: Hybrid (not fully remote or onsite exclusively).
Experienced in architecting complex AI/ML systems with a focus on Generative AI and commercial data applications.
Operates at a senior technical leadership level, combining hands-on coding with strategic technical decision-making and cross-functional collaboration.
Capable of pioneering advanced AI solutions including RAG, multi-agent frameworks, vector databases, and responsible AI practices within a large enterprise setting.