Data Engineer - Agentic AI & ML Ops (Co-op)

Operational Support Data Engineer – Agentic AI & ML Ops (Co-op) We are seeking a motivated and curious Data Engineer – Agentic AI & ML Ops to join our Enterprise Data & Analytics team. This co-op provides hands‑on experience supporting cloud‑based data platforms, AI/ML operations, Generative AI, and Agentic AI solutions. You will work with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, Python, PySpark, SQL, LLMs, and modern AI/ML frameworks in an Agile environment. If you are passionate about data engineering, AI, and automation, we want to hear from you. Key Responsibilities Build Data & AI Pipelines: Develop and support ETL/ELT pipelines and AI/ML workflows. Data Integration & Transformation: Ingest, transform, and orchestrate data using Python, PySpark, and SQL. Develop Agentic AI Solutions: Build and test AI agents and intelligent workflows for automation and data access. LLM & Prompt Engineering: Design and optimize prompts and workflows using LLMs and GenAI frameworks. AI/ML Development & Automation: Build Python‑based scripts, APIs, and notebooks on cloud platforms. Support Analytics & AI/ML: Prepare datasets for reporting, ML models, forecasting, and advanced analytics. Monitor & Support Operations: Troubleshoot pipeline failures, performance issues, and data quality gaps. MLOps & CI/CD: Support deployment, testing, and automation for data and AI solutions. Data Modeling & Semantic Layers: Assist with STTM, data modeling, and reporting datasets. Agile Collaboration: Participate in sprint planning, stand‑ups, and retrospectives. Documentation & Automation: Create runbooks, workflows, and technical documentation. Learning & Development Opportunities Hands‑on experience with Databricks, Snowflake, Azure, ADLS, ADF, and Power BI. Exposure to MLOps, GenAI, Agentic AI, LLMs, CI/CD, and automation. Experience working with AI agents, prompt engineering, and workflow orchestration. Mentorship from Data, AI/ML, and Platform Engineers. Experience in Agile/Scrum and DevOps/MLOps environments. Qualifications Pursuing a degree in Computer Science, Data Engineering, Data Science, AI/ML, or related field. Knowledge of SQL, Python/PySpark, ETL/ELT, and APIs. Familiarity with Databricks, Snowflake, Azure, ADLS, ADF, Power BI, or Git is a plus. Exposure to LLMs, GenAI, Agentic AI, MLOps, or CI/CD is beneficial. Experience with Python‑based AI/ML projects or notebooks is a plus. Strong analytical and problem‑solving skills. Strong communication and teamwork skills. 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. #J-18808-Ljbffr The Campbell's Company