Agentic AI Engineer Co-Op

The Campbell's Company; United States; On-site; USD 100,000 - 150,000; Full time

Job summary

The Campbell's Company is seeking an Agentic AI Engineer to design, build, and deploy autonomous AI systems that reason, plan, and execute complex workflows. This role involves developing intelligent agents that integrate models, tools, and memory, enhancing task execution.

As an AI Engineer, you'll work on agent orchestration, design Retrieval-Augmented Generation pipelines, and ensure production deployment in cloud environments. A strong background in AI/ML is essential. Equal opportunity commitment is prioritized in the hiring process.

Qualifications

• 2+ years in AI/ML system design, deployment, or autonomous agent development.
• Proficiency in Python, Java, and C#.
• Experience with agent orchestration frameworks.

Responsibilities

• Design and develop autonomous agentic systems.
• Implement agent orchestration using frameworks.
• Handle tool and memory integration for AI agents.

Skills

Python

Java

C#

Agent orchestration frameworks

Multi-agent communication protocols

RAG architectures

Cloud platforms (Azure, AWS)

CI/CD pipelines

Job description

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), multimodal 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.

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.