Manager - AI Integration & Agentic Analytics Engineering

Our client is seeking a Manager, AI Integration & Agentic Analytics Engineering to lead the design, development, and delivery of next-generation enterprise data products, AI-powered analytics, and intelligent automation solutions. This leader will oversee a team of analytics engineers, data engineers, and AI developers focused on modern cloud data platforms, enterprise integrations, and agentic AI capabilities that drive business efficiency and decision-making. This role combines strategic leadership with deep technical expertise across data engineering, reporting architecture, cloud platforms, AI technologies, enterprise integrations, and financial analytics., Leadership & Team Development

• Foster a culture of innovation, technical excellence, and continuous improvement.
• Coach teams on modern software engineering practices and AI-assisted development methodologies.
• Drive technical strategy, roadmap planning, and execution across multiple enterprise initiatives.
• Partner closely with Product, Architecture, Security, Finance, Operations, and business stakeholders.

AI & Intelligent Automation

• Lead adoption and implementation of enterprise AI technologies, including:
• AI Agents
• Multi-agent workflows
• LLM orchestration
• Retrieval-Augmented Generation (RAG)
• Model Context Protocol (MCP)
• Prompt engineering
• Agent evaluation frameworks
• Human-in-the-loop AI systems
• Identify opportunities to automate reporting, analytics, and business processes through AI-driven solutions.
• Develop reusable AI capabilities that improve engineering productivity and accelerate business outcomes.
• Enable intelligent workflow automation and AI-assisted software development practices.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• Significant experience leading technical engineering teams.
• Strong background delivering enterprise-scale data platforms and analytics solutions.
• Experience integrating and managing enterprise source systems.
• Expertise in cloud-based data engineering environments.
• Strong proficiency in SQL and Python.
• Experience building scalable reporting and analytics solutions.
• Strong understanding of dimensional data modeling methodologies.
• Experience supporting financial reporting and enterprise analytics initiatives.
• Experience developing and consuming APIs and enterprise integrations.
• Excellent communication, leadership, and stakeholder management skills.