Senior Agentic AI Engineer

Ingram Micro is a leading technology company for the global information technology ecosystem. They are seeking a talented and motivated Agentic AI Engineer to design, develop, test, and deploy AI agents that can perceive their environment and make autonomous decisions, working closely with AI Architects and Data Scientists.

Responsibilities:

• Lead Agent Architecture & Development: Lead the end-to-end design, development, and deployment of complex, scalable, and secure enterprise-grade AI agents. Define the architectural patterns and technical standards for agentic systems across the organization
• Strategic System Integration: Architect and oversee the integration of AI agents with critical enterprise systems (ERP, CRM, SCM, WMS), ensuring robust data flows and operational efficiency
• Own Core Functionality & Innovation: Drive the development and implementation of advanced agent functionalities, including sophisticated reasoning chains, multi-agent collaboration, long-term memory, and dynamic tool creation
• Code Excellence & Mentorship: Champion and enforce standards for clean, highly efficient, well-documented, and rigorously tested code. Mentor junior and mid-level engineers in advanced programming techniques and best practices
• Architectural Partnership: Partner with AI Architects and business stakeholders to translate strategic objectives and architectural blueprints into tangible, high-impact AI solutions
• Cross-Functional Leadership: Act as a key technical leader in collaborations with Data Scientists, Platform Engineers, and Product Managers, guiding the analytical approach and ensuring the rigorous application of statistical methods in AI/ML models
• Drive Prototyping & Feasibility: Lead the ideation and development of innovative prototypes and proof-of-concepts to demonstrate the art of the possible, de-risk new technologies, and validate complex analytical approaches
• Agile Process Improvement: Guide and improve agile development practices within the team, enhancing velocity and outcomes in sprint planning, stand-ups, and reviews
• Lead Experimentation & Validation Strategy: Design and implement comprehensive A/B testing and experimentation frameworks to validate agent performance and drive data-driven decisions. Establish rigorous statistical benchmarks for model reliability, accuracy, and business impact
• Own Model Lifecycle & Analysis: Take ownership of the analytical aspects of the model lifecycle, from feature engineering and selection to post-deployment performance analysis. Conduct deep-dive analyses to understand model behavior and identify opportunities for improvement
• Advanced Troubleshooting & Root Cause Analysis: Serve as the escalation point for complex issues related to model performance and data drift. Utilize advanced statistical analysis to diagnose root causes and implement robust, long-term solutions
• Continuous Learning & Evangelism: Stay at the forefront of advancements in agentic AI, LLMs, and statistical learning theory, and act as a subject matter expert, evangelizing new analytical techniques and methodologies within the AI CoE
• Process & Standards Definition: Drive the continuous improvement and definition of the CoE's agent development processes, analytical tools, and validation standards
• Mentor & Develop Talent: Actively mentor and coach junior and mid-level AI Engineers and Data Scientists, fostering their technical growth and contributions to the team