AI Data Engineer Co-op — Generative AI & Automation

Campbell Soup Company

Camden (NJ)

On-site

USD 52,000 - 70,000

Full time

14 days+
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Benefits offered by this job

Hands-on AI training
Mentorship from senior AI Engineers
Experience with Azure/Databricks/Snowfl
Databricks environment exposure

Job summary

Campbell Soup Company is seeking a Data Engineer / AI Engineer co-op to gain hands-on experience with Generative AI in a modern Databricks environment. You will prototype AI agents, train and tune models, and collaborate with cross-functional teams to integrate AI capabilities into enterprise applications.

The role emphasizes hands-on learning, mentorship from senior AI and data scientists, and practical work with cloud/SaaS infrastructure such as Azure, Databricks, and Snowflake.

Qualifications

  • Current graduate student pursuing CS/DS/AI/Math or related field.
  • Foundational Python and SQL skills with curiosity for AI methods.
  • Interest in generative AI, data workflows, and modern cloud data platforms.

Responsibilities

  • Prototype AI agents to automate internal workflows and data retrieval.
  • Provide feedback to improve AI agent training and outputs.
  • Fine-tune prompts and system prompts for reliability.
  • Monitor model performance and identify issues in AI outputs.
  • Collaborate with cross-functional teams in Agile ceremonies.
  • Explore new AI tools under guidance of senior engineers.
  • Document model architectures, APIs, and governance standards.

Skills

Python
SQL
AI concepts
Problem solving
Curiosity

Education

Graduate student in CS/DS/AI/Math

Tools

Azure
Databricks
Snowflake

Job description

Campbell Soup Company is seeking a Data Engineer / AI Engineer co-op to gain hands-on experience with Generative AI in a modern Databricks environment. You will prototype AI agents, train and tune models, and collaborate with cross-functional teams to integrate AI capabilities into enterprise applications.

The role emphasizes hands-on learning, mentorship from senior AI and data scientists, and practical work with cloud/SaaS infrastructure such as Azure, Databricks, and Snowflake.

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