AI Technical Lead – Chief Manager, Application

About the role

The AI Technical Lead will serve as the technical backbone of the AI Center of Excellence, designing scalable AI architectures and delivering enterprise‑grade AI solutions. This senior, hands‑on leader will mentor engineering teams while collaborating closely with business, product, and enterprise architecture stakeholders.

Key responsibilities

• Design and implement secure, production‑ready AI solution architectures and define enterprise AI reference standards.
• Build reusable AI frameworks, accelerators, and shared services; evaluate and select appropriate models, frameworks, and technologies.
• Lead the development of generative AI applications such as AI copilots, customer service assistants, loan underwriting bots, and multi‑agent workflow agents.
• Guide the creation, optimization, deployment, and monitoring of predictive and classification models, recommendation engines, fraud detection, credit scoring, and NLP solutions.
• Partner with MLOps teams to build scalable AI platforms, develop APIs and micro‑services, and manage model versioning, lifecycle, and observability.
• Drive AI integration with enterprise systems including CRM, loan origination, mobile apps, data lakes, and API gateways.

Required profile

• Senior technology leader with extensive experience in Generative AI, LLMs, and Retrieval‑Augmented Generation.
• Proven track record of architecting and delivering enterprise AI solutions at scale.
• Strong mentorship skills and ability to lead cross‑functional AI engineering teams.
• Deep understanding of enterprise architecture, cybersecurity, and governance standards.

Required skills

• Generative AI and Large Language Models (LLMs)
• Retrieval‑Augmented Generation (RAG) and Prompt Engineering
• Semantic Search, Vector Databases, and Agent Orchestration
• Machine Learning, Predictive Modeling, Classification, Recommendation Systems, NLP, Time‑Series Forecasting
• MLOps, AI Platform development, API design, Micro‑services
• Cloud platforms (AWS, Azure, GCP) and enterprise integration patterns