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Tier-1 employer and metro location increase applicant density despite senior, specialized role.
Requires deep applied AI and enterprise finance platform experience, making cross-industry transferability limited.
Explicit 15+ years, leadership and deep AI/ML/platform experience indicate stringent screening and technical filters.
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Lead design, development, and scaling of AI infrastructure and multi-agent workflows, focusing on LLM-powered capabilities integration.
Own end-to-end lifecycle of AI applications including data pipelines, backend services, platform integration, and deployment using Agile methodologies.
Establish AI engineering best practices, evaluation frameworks, and governance standards to optimize big data ecosystem performance in a regulated environment.
Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, AI/ML, or related quantitative field.
15+ years’ experience building and deploying engineering, AI, or ML systems end-to-end, with recent experience delivering LLM-based applications in production.
3+ years’ experience leading teams or large-scale cross-functional initiatives with proven technical leadership and delivery.
Strong proficiency in Python, AI/ML frameworks (PyTorch, TensorFlow), experience with agentic orchestration frameworks (e.g., LangGraph), and cloud-native deployment environments.
Experienced strategic leader capable of translating business priorities into scalable AI technical solutions and leading complex technical programs.
Hands-on expert in AI system design and deployment, especially LLM-based workflows and advanced NLP concepts, operating effectively across strategy and execution.
Demonstrated ability to build and mentor high-performing engineering teams, prioritizing platform scalability, engineering rigor, and responsible AI governance in regulated enterprise settings.