Agentic AI Engineer Co-Op
Campbellsoup Open · verified Oct 22, 2026 At a glance
Junior AI Engineering role at Campbellsoup. Remote, United States · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build AI agents that plan, reason and complete multi-step tasks using models, tools and business rules
- Set up agent workflows with orchestration frameworks, then connect agents to APIs, databases and memory
- Create RAG pipelines by preparing documents, generating embeddings and improving how relevant information is retrieved
- Measure agent accuracy, grounding, speed and cost, and track behavior and failure patterns
- Adapt foundation models and deploy agent systems with CI/CD, version control and runtime safeguards
What you bring
- At least two years designing or deploying AI/ML systems, or developing autonomous agents
- You can build AI/ML solutions in Python and have used agent frameworks and multi-agent communication methods
- Hands-on work integrating LLMs with RAG, including ways to assess results
- Experience with cloud platforms and CI/CD, plus knowledge of responsible AI, security and compliance
Who this fits
This junior co-op suits someone ready to apply AI/ML engineering skills to autonomous agents and production deployment. The role is remote in the United States.
From the employer
Since 1869, we've connected people through food they love. We’re proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell’s brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao’s Homemade, Snack Factory, Snyder’s of Hanover. Swanson, and V8.
Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.
An Agentic AI Engineer designs, builds, and deploys autonomous AI systems that can reason, plan, use tools, and execute multi-step workflows with minimal human intervention . Unlike traditional AI/ML engineers who focus on model training and prediction, agentic AI engineers orchestrate goal-driven workflows that integrate models, tools, memory, and business logic to achieve objectives dynamically
Core Responsibilities
• 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
Required Skills & Experience
• 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)
The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.