Armonk, United States Role overview
About this role
We are looking for motivated, curious, and technically strong software engineering interns to join our team this summer. You will work closely with senior engineers to design, build, and test next‑generation agentic AI capabilities and automated workflows that support data and engineering operations at scale. This internship is ideal for students who enjoy hands‑on development, exploring emerging AI patterns, and building real systems that will be used across the enterprise. As a Software Engineering Intern, you will: Develop Python-based services, agents, and tooling to support AI workflows and automation. Help design and prototype agentic AI patterns (reasoning agents, workflow planners, retrieval pipelines, evaluation harnesses, etc.). Contribute to backend engineering tasks such as API development, orchestration logic, and system integration. Build, configure, and test AI workflows running on modern platforms (Kubernetes, vector databases such as Milvus, distributed systems). Collaborate with other engineers to refine requirements, troubleshoot issues, and improve system performance. Document your designs, experiments, and findings in clear engineering artifacts. Participate in Agile ceremonies (standups, sprint planning, demos) and contribute to a fast-paced engineering culture. Who You Are A student pursuing a degree in Computer Science, Software Engineering, Data Science, or a related field. A self-starter who enjoys solving complex problems and experimenting with new ideas. Someone excited about the rapidly evolving world of AI agents and workflow automation. Enthusiastic about learning from experienced engineers and contributing to real-world systems. What You’ll Gain Hands-on experience with cutting-edge agentic AI technologies. Mentorship from senior engineers and engineering managers. Real ownership of impactful engineering deliverables. Exposure to enterprise-scale data platforms and AI infrastructure. A chance to grow your technical skills and professional network. Strong proficiency in Python, including experience with common libraries such as requests, pydantic, pandas, or asyncio. Solid understanding of software engineering fundamentals: data structures, algorithms, debugging, testing. Familiarity with REST APIs, microservices, or event-driven systems. Curiosity and willingness to explore agentic AI, LLMs, and workflow automation frameworks. Ability to work collaboratively in a team environment. You do not need all of these, but experience with any is a plus: Experience with AI/ML libraries (OpenAI SDK, LangChain, Hugging Face, or similar). Exposure to Kubernetes, Docker, or cloud-native environments. Understanding of vector databases (e.g., Milvus, Pinecone, Weaviate). Knowledge of asynchronous programming or distributed systems. Experience building data pipelines or workflow orchestration tools. Familiarity with Git, CI/CD, and modern engineering practices.