Competitive Intelligence AI Engineering Intern - Summer 2027
As an AI Engineering Intern for the Competitive Intelligence team, you will design, develop, and manage AI tools to enhance market research and competitive analysis processes.
We are building cutting-edge AI systems that enable the next generation of intelligent applications. Our team focuses on developing AI agents, benchmarking datasets, and robust infrastructure to support real-world deployments at scale. As part of our engineering-driven culture, you'll be exposed to a fast-paced environment where experimentation, collaboration, and innovation are encouraged.
- Contribute to the design and development of AI agents integrated into live systems.
- Help build and maintain benchmark datasets to evaluate AI performance.
- Implement, test, and optimize backend services in Python or Golang.
- Collaborate closely with senior engineers on system design, multi-agent orchestration, and deployment
- Participate in code reviews, debugging, and documentation to ensure best practices.
- Work in a team environment that encourages mentorship, knowledge sharing, and hands-on learning
- Currently pursuing a degree in Computer Science, Software Engineering, or a related field
- Strong programming fundamentals — language-agnostic, but practical experience with at least one of Python, Go, TypeScript, or similar
- Solid understanding of software engineering principles (data structures, algorithms, version control)
- Familiarity or working knowledge of any AI agent framework (e.g., OpenClaw, hermes-agent, LangChain, CrewAI, AutoGen)
- Interest in AI, data-driven systems, and building tools for real-world applications
- Good communication skills and willingness to learn quickly
- AI-native working style — you naturally reach for AI tools in your daily workflow, not as an afterthought but as a core part of how you think, build, and solve problems
- Eager to learn and open-minded — you stay current with the latest technologies and aren't afraid to adopt new frameworks, tools, or paradigms before they're mainstream
- First-principles thinker who's comfortable redesigning workflows rather than just optimizing existing ones
- Experience with LLMs, prompt engineering, or building tools on top of AI models
- Exposure to multi-agent systems or agent orchestration patterns
- Familiarity with Docker, cloud platforms, or CI/CD pipelines
- Machine learning knowledge is a plus, but not required
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