Agentic AI Developer Intern

Job Target is a leading company in the online job search and recruiting industry. Our team iscomprisedof experts in recruitment, e-commerce, and online job search. Our products are used by thousands of corporate recruiters and reach millions of job seekers. The company values work-life balance, rewarding risk and creativity, and an open culture. driven, and open-minded.

We'reperpetually searching forways to make the job search process better, so ifyou'reup for the challenge, apply, andlet'smake it better together.

We are looking for a motivated Generative AI Developer Intern to join our AI Engineering Team. In this role, you will help design, build, test, and improve AI-powered applications and internal tools using modern software engineering practices. You will work closely with software engineers, AI/ML engineers, product managers, and data teams to develop prototypes, integrate large language models, build APIs, evaluate model outputs, and contribute to production-quality AI features.

This internship is ideal for students or recent graduates with a strong computer science background, solid coding skills, and an interest in building practical applications using generative AI technologies. Must be able to work at least 30 hours a week.

• Develop and maintain AI-powered software features, prototypes, and internal tools.
• Write clean, efficient, and well-documented code in Python or another modern programming language.
• Integrate large language models and AI APIs into applications, workflows, or backend services.
• Assist in building retrieval-augmented generation, prompt workflows, model evaluation pipelines, and AI agent workflows.
• Support development of agentic AI applications using frameworks such as Lang Graph, Lang Chain, or similar tools.
• Collaborate with engineers to design APIs, services, and data flows that support AI applications.
• Test, debug, and improve AI system behavior, including accuracy, reliability, latency, and usability.
• Participate in code reviews, unit testing, documentation, and deployment activities.
• Help evaluate AI outputs for quality, consistency, safety, and business usefulness.
• Work with structured and unstructured data, including text, documents, logs, or user-generated content.
• Stay current with emerging AI development tools, frameworks, and best practices.

• Currently pursuing a Bachelor’s or Master’s degree (preferred) in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
• Solid understanding of data structures, algorithms, object-oriented programming, and software engineering fundamentals.
• Experience building software projects, APIs, applications, automation scripts, or backend services.
• Familiarity with REST APIs, JSON, Git, and basic cloud or deployment concepts.
• Strong analytical and problem-solving skills.
• Ability to learn quickly, communicate clearly, and work well in a collaborative engineering environment.

• Experience with generative AI tools, LLM APIs, or AI application frameworks.
• Familiarity with tools or concepts such as OpenAI, Anthropic, Gemini, Azure OpenAI, or similar LLM platforms Lang Graph, Lang Chain, Llama Index, Semantic Kernel, or similar AI application frameworks.
• Experience with AI agents, multi-step workflows, tool calling, memory, routing, or orchestration patterns.
• Vector databases such as Pinecone, Weaviate, Chroma, FAISS, or pgvector.
• Retrieval-augmented generation, embeddings, prompt engineering, or model evaluation.
• FastAPI, Flask, Node.js, React, or similar application frameworks.
• Docker, CI/CD, cloud platforms, or basic Dev Ops workflows.
• Experience with machine learning frameworks such as PyTorch, Tensor Flow, or scikit-learn.
• Experience working on academic, personal, open-source, or internship projects involving AI, ML, NLP, automation, or software development.
• Interest in responsible AI, model evaluation, privacy, security, and safe AI deployment.

• How to build real-world generative AI applications and AI-powered developer tools.
• How to integrate LLMs into software systems using APIs, embeddings, retrieval, and evaluation workflows.
• How to design AI agent workflows using tools such as Lang Graph and related frameworks.
• Best practices for writing production-quality code for AI applications.
• How to test and improve AI system reliability, accuracy, and performance.
• How AI engineering teams collaborate across product, data, software, and infrastructure functions.
• Practical exposure to modern AI development frameworks, cloud tools, and deployment practices.

Hourly pay range: $27.00 - $30.00.

Job Target is an equal-opportunity employer.