Kimberly Clerk is hiring for the role of Gen AI Intern, a technical internship focused on delivering agentic AI solutions with a clear emphasis on safety, mutual respect, and human dignity. The position centers on building components for Supply Chain applications, requiring hands-on development of agents that leverage large language models (LLMs) and open source frameworks. Candidates are expected to translate business requirements into agent implementations and to ensure that those agents meet necessary accuracy expectations. This announcement highlights a focused technical responsibility combined with an ethical approach to AI development.
Role overview and mission
Core focus and intent
The Gen AI Intern role is framed as a technical position where the primary objective is to succeed with consumers and the market while centering safety and respect in all development work. The role asks the intern to keep safety, mutual respect, and human dignity at the core of their approach when designing and implementing AI-driven components. This ethical emphasis is stated alongside the technical expectations, signaling that technical solutions should align with principled considerations.
Scope of the position
This internship focuses on development tasks tied to Supply Chain agentic AI components. The intern will be expected to deliver tangible, hands-on work that contributes to such components, working with LLMs and open source frameworks to build agents that respond to business needs. A clear requirement is translating business requirements into functioning agents and ensuring those agents meet defined accuracy goals.
How responsibilities connect
- Maintain a market- and consumer-oriented perspective while developing technical solutions.
- Embed safety and respect for human dignity into agent behavior and design decisions.
- Convert business requirements into agent designs and implementations that satisfy accuracy requirements.
Technical responsibilities: building agentic AI for Supply Chain
Hands-on agent development
The position emphasizes being hands-on in developing agents that leverage LLMs and open source frameworks. Interns are expected to actively participate in the coding, testing, and iterative refinement of agentic components rather than only contributing at a conceptual level. The hands-on nature indicates practical development work using code and frameworks commonly associated with LLM-based agents.
Alignment with business requirements
Beyond pure technical implementation, a critical part of the role is understanding and addressing business requirements. The intern must interpret what the business needs and then design or implement agents that meet those needs effectively. Ensuring that agents achieve required levels of accuracy is explicitly called out as a deliverable within this context.
What “LLMs and open source frameworks” implies
- Work will involve large language models as a core element for agent capabilities.
- Open source frameworks will be used alongside LLMs to structure agent behavior and workflows.
- Practical development, testing, and refinement of agents are expected rather than purely theoretical contributions.
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Required qualifications and skills
Educational background
The role specifies a BTech in Engineering in computer science, data science, AI, or allied branches as the required educational qualification. This degree requirement indicates a preference for candidates with formal technical training aligned with core computing, data, or AI disciplines. The listing does not specify additional educational endorsements beyond the BTech requirements.
Technical skills and coding experience
Candidates must have hands-on development experience with coding languages such as Java, Python, NodeJS, or similar languages. The listing highlights practical, not purely theoretical, coding experience—meaning demonstrable development work is part of the expectation. Exposure to AI and machine learning is also required, indicating familiarity with AI concepts or applied ML workflows.
Key qualifications summarized
- BTech in computer science, data science, AI, or allied engineering branches.
- Hands-on development experience in coding languages like Java, Python, NodeJS.
- Exposure to AI and machine learning concepts or applications.
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How to prepare and align with the internship expectations
Practical preparation focus
Preparation for this Gen AI Intern role should emphasize hands-on coding and practical exposure to AI-related tools. Given the explicit need to develop agents using LLMs and open source frameworks, it is important to practice implementing agent behaviors, testing outputs, and iterating toward acceptable accuracy. Preparation efforts that mirror the hands-on, implementation-oriented nature of the role will align best with the stated responsibilities.
Skill areas to prioritize
- Strengthen programming proficiency in languages such as Java, Python, or NodeJS through practical projects.
- Gain exposure to AI and machine learning workflows, focusing on how models are used within agent systems.
- Practice interpreting business requirements and translating them into technical implementations with measurable accuracy goals.
Supportive resources and time management
While the role itself is technical and development-focused, managing time effectively will support sustained hands-on work and iterative development cycles. Combining coding practice, AI exposure, and disciplined time management will help applicants meet the combined technical and ethical expectations. For additional learning, there are publicly available tutorials and programs that can complement hands-on practice with structured content.
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Frequently Asked Questions
What is the Gen AI Intern role at Kimberly Clerk?
The Gen AI Intern position is a technical internship focused on building agentic AI components for Supply Chain. The role requires hands-on development of agents using large language models and open source frameworks while centering safety, mutual respect, and human dignity in the work.
What are the main responsibilities of the intern?
Key responsibilities include developing agentic AI components for Supply Chain, working hands-on with LLMs and open source frameworks, understanding business requirements, and ensuring that agent implementations meet required accuracy levels. The role also emphasizes winning with consumers and the market while prioritizing safety and respect.
What educational qualifications are required?
Candidates must hold a BTech in Engineering in computer science, data science, AI, or allied branches. This educational requirement reflects the technical nature of the internship and the expectation of foundational engineering and computing knowledge.
Which programming languages and technical exposures are expected?
Applicants should have hands-on development experience in coding languages such as Java, Python, or NodeJS. The role also requires exposure to AI and machine learning, indicating familiarity with AI concepts and applied ML workflows that support agent development.
How does the role address ethical considerations?
The internship explicitly places safety, mutual respect, and human dignity at the center of its work. These ethical considerations are presented as integral to the technical responsibilities, so implementations and agent behaviors should reflect those principles throughout development.
In summary, Kimberly Clerk’s Gen AI Intern position combines focused technical development with an explicit ethical mandate. Candidates with a BTech in relevant engineering fields, hands-on coding experience in languages like Java, Python, or NodeJS, and exposure to AI and machine learning are positioned to meet the stated requirements. The role expects practical, hands-on development of agents using LLMs and open source frameworks, alongside translating business requirements into accurate agent implementations. This internship underscores an approach that balances market and consumer success with safety, mutual respect, and human dignity.
