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Metro location and popular AI role increase competition despite specialized skills.
Highly domain-specific AI architecture skills limit transferability across non-AI industries.
Explicit 8+ years and 3+ years AI architecture requirement with specific tech mandates.
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Lead design and implementation of end-to-end AI/ML architectures including Generative AI and Agentic AI.
Drive AI platform development using cloud services like Azure, AWS, or GCP and develop scalable AI applications using Python, LLMs, RAG, Vector Databases, and ML Ops.
Collaborate with business stakeholders to identify AI use cases and ensure AI governance, security, and compliance while mentoring engineering teams on AI initiatives.
8+ years of software engineering experience with at least 3 years in AI/ML architecture.
Bachelor's or Master's degree in Computer Science, IT, AI, or related fields.
Hands-on experience with Python, Machine Learning, Deep Learning, NLP, Generative AI, Azure AI, AWS SageMaker, OpenAI APIs, Lang Chain, and Vector Databases.
Knowledge of CI/CD, Docker, Kubernetes, and ML Ops tools.
Proven ability to lead AI strategy and digital transformation through scalable and secure AI/ML architecture design.
Experience working with enterprise AI solutions and deploying them in cloud environments (Azure, AWS, GCP).
Comfortable managing cross-functional collaboration with business stakeholders and mentoring technical teams on AI initiatives.