Lead AI Engineer: Agentic AI & Enterprise Integration

PepsiCo

Chicago (IL)

On-site

USD 124,000 - 207,000

Full time

4 days ago
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Benefits offered by this job

Medical, Dental, Vision
Defined Contribution Retirement Plan
Paid time off & parental leave

Job summary

PepsiCo is seeking an experienced Forward Deployed AI Engineering Lead to design and deliver production-grade agent capabilities across cloud and edge environments. You will translate complex business workflows into measurable agent outcomes, drive adoption with transformation teams, and partner with enterprise platform owners to scale solutions.

The role focuses on architecture, implementation, and governance of multi-agent systems, integration patterns, and evaluation frameworks within client

Qualifications

  • Bachelor’s degree in CS/AI/ML or equivalent experience.
  • Master’s degree preferred.
  • 12+ years of experience with the software lifecycle.
  • Expertise in ML development and engineering including production-grade large language models and agent systems.
  • Proven experience shipping LLM/agent solutions to production with measurable quality.

Responsibilities

  • Architect and deploy AI agent solutions directly in client environments.
  • Customize agent patterns to solve business challenges across client tech stacks.
  • Transform ambiguous requirements into production-ready solutions with minimal iterations.
  • Drive performance optimization (latency, reliability) in client infrastructures.
  • Lead complex integrations between AI capabilities and client systems.

Skills

Python
Java
Distributed systems
Multi-agent systems
LangChain
LangGraph
CrewAI
Docker
Kubernetes
Ray
FastAPI
Pydantic

Education

Bachelor’s in CS/AI/ML
Master’s preferred

Tools

LangChain
LangGraph
CrewAI
Docker
Kubernetes
Ray
FastAPI
Pydantic

Job description

PepsiCo is seeking an experienced Forward Deployed AI Engineering Lead to design and deliver production-grade agent capabilities across cloud and edge environments. You will translate complex business workflows into measurable agent outcomes, drive adoption with transformation teams, and partner with enterprise platform owners to scale solutions.

The role focuses on architecture, implementation, and governance of multi-agent systems, integration patterns, and evaluation frameworks within client

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