AI Engineer Co-Op

Campbell's

Agentic AI Engineer designing and deploying autonomous AI systems at a food industry leader. Focused on intelligent agents and AI workflows for enhanced business solutions.

Posted 6/17/2026full-timeRemote • 🇺🇸 United StatesEntry LevelWebsite

Tech Stack

Tools & technologies

AWSAzureCloudJavaPython

About the role

Key responsibilities & impact

Design & Develop Agentic Systems: Build intelligent agents capable of autonomous planning, reasoning, and task execution, often using LLMs (e.g., GPT-class, LLaMA), multi-modal models, and autonomous workflows
Orchestration & Frameworks: Implement agent orchestration using frameworks like LangChain, AutoGen, CrewAI, Semantic Kernel, or custom solutions
Retrieval-Augmented Generation (RAG): Design and optimize RAG pipelines for enhanced reasoning with external knowledge, including document ingestion, chunking, embeddings, vector stores, and retrieval ranking
Tool & Memory Integration: Develop agents that call APIs, databases, and other tools, maintain memory, and adapt based on outcomes
Evaluation & Monitoring: Create evaluation frameworks for accuracy, grounding, latency, and cost; build observability for agent behavior and failure modes
Model Adaptation: Fine-tune or adapt foundation models (e.g., via LoRA, adapters) for domain-specific use cases
Production Deployment: Deploy GenAI/agentic systems in cloud-native environments with CI/CD, versioning, and runtime safeguards
Cross-Functional Collaboration: Work with data scientists, ML engineers, product teams, and governance/compliance stakeholders

Requirements

What you’ll need

2+ years in AI/ML system design, deployment, or autonomous agent development
Programming: Proficiency in Python (and sometimes Java, C#) for AI/ML solution development
Agent & Workflow Expertise: Experience with agent orchestration frameworks and multi-agent communication protocols
RAG & LLM Integration: Hands-on with RAG architectures, evaluation methodologies, and LLM integration
Cloud & DevOps: Experience with cloud platforms (e.g., Azure, AWS) and CI/CD pipelines
Governance & Compliance: Understanding of responsible AI, security, and compliance in regulated domains (e.g., retail)

Benefits

Comp & perks

Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonJavaC#agent orchestrationRAG pipelinesLLM integrationmodel fine-tuningcloud-native deploymentCI/CDevaluation methodologies

Soft Skills

cross-functional collaboration