Lead AI Engineer

Overview

As a Forward Deployed AI Engineering Lead specializing in Agentic AI enablement, you will lead the design and delivery of production-grade agent capabilities built on the enterprise AI Backbone across cloud and edge environments – across supply‑chain and global functions. You will own end‑to‑end delivery of key agentic modules and integration patterns (MCP/tooling), establish strong evaluation and regression discipline, and drive adoption by embedding within transformation teams and BU and partnering with platform engineering and enterprise application owners.

You serve as a technical anchor for the workstream—translating ambiguous business workflows into measurable agent outcomes, proactively identifying risks, proposing options/tradeoffs, and ensuring solutions scale across domains.

BU Facing Solution Architecture & Implementation - (40%):

• Architect and deploy transformative AI agent solutions directly in client environments, adapting core technologies to unique client constraints and infrastructure. (Lead/Execute)
• Rapidly customize agent patterns (tool integrations, enterprise system connections, security models) to solve high‑impact business challenges across diverse client tech stacks. (Lead/Execute)
• Transform ambiguous client requirements into production‑ready solutions with minimal iterations through exceptional technical discovery skills. (Lead)
• Drive on‑site performance optimization beyond client expectations (latency, reliability, throughput) while working within client infrastructure limitations. (Execute/Lead)
• Establish implementation playbooks that accelerate future deployments and enable customer success teams to scale. (Lead)

Field‑Based Quality Engineering & Diagnostics - (20%):

• Design and implement BU and function‑specific evaluation frameworks that validate solution effectiveness in production environments with real data. (Lead/Execute)
• Develop rapid diagnostic methodologies to identify and resolve critical issues during implementation without disrupting client operations. (Execute/Lead)
• Create monitoring systems that provide early warning of edge cases and performance degradation unique to each deployment environment. (Execute)
• Perform advanced troubleshooting in constrained client environments where standard tools may be unavailable. (Execute/Lead)
• Establish quality baselines that enable clients to self‑monitor system health post‑implementation. (Execute/Lead)

Function‑Specific Model Optimization & Adaptation - (15%):

• Fine‑tune model selection and routing strategies based on function‑specific data characteristics and performance requirements. (Lead/Execute)
• Optimize prompt engineering for unique BU domains, creating specialized techniques that overcome domain‑specific challenges. (Execute/Lead)
• Implement model adaptation techniques that improve performance with minimal additional client data. (Execute)
• Develop function‑ready evaluation frameworks that demonstrate model effectiveness to technical and business stakeholders. (Lead)

Enterprise Systems Integration & Data Flow Engineering - (15%):

• Lead complex integrations between AI capabilities and diverse client systems (ERPs, CRMs, legacy databases, custom applications). (Lead/Execute)
• Design and implement secure data pipelines that respect client compliance requirements while enabling AI functionality. (Execute/Lead)
• Create adapter patterns that isolate core AI functionality from client‑specific integration complexities. (Lead)
• Develop client‑specific documentation and knowledge transfer protocols that enable client teams to maintain integrations independently. (Execute/Lead)

Client Success & Implementation Leadership -(10%):

• Serve as the primary technical bridge between core engineering and client stakeholders, translating between business needs and technical capabilities. (Lead)
• Mentor client technical teams to build internal AI implementation capabilities. (Lead)
• Drive adoption through hands‑on workshops, knowledge transfer sessions, and executive‑level capability demonstrations. (Lead/Execute)
• Identify expansion opportunities through deep understanding of client's technical landscape and business challenges. (Lead)
• Commu…