AI Engineering Intern

About the role

As an AI Engineering Intern, you will be at the forefront of applying generative AI to enhance Pindrop's internal operations and engineering productivity. You will work closely with senior engineers to turn manual processes into intelligent, automated workflows.

What you'll do

• Explore and build proof-of-concept AI agents to automate complex internal engineering workflows, such as incident analysis or code review summaries.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines to enable "chat with your data" capabilities for internal technical documentation and runbooks.
• Collaborate with cross-functional teams to identify operational bottlenecks and implement AI-driven fixes that improve efficiency and performance.
• Test and document the use of emerging AI-assisted coding and monitoring tools to determine their viability for the broader engineering organization.
• Participate in security-minded engineering, ensuring that automated workflows follow strict data hygiene and secrets management protocols.

Who you are

• Deeply curious about how AI can make large-scale systems more efficient and comfortable experimenting with new, unproven tools.
• Excited to uncover innovative solutions and can teach yourself new frameworks (like LangChain or Auto-GPT) when needed.
• Take ownership of your projects, under-promise, and over-deliver.
• Seek feedback frequently and can explain complex AI concepts to both technical and non-technical teammates.

Must-haves

• Pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related technical field.
• Knowledge of Python for automation and data processing.
• Demonstrated interest or project experience in AI/ML, specifically involving Large Language Models (LLMs) and prompt engineering.
• Familiarity with Git workflows.

Nice-to-haves

• Hands-on experience building small ML pipelines or experimenting with vector databases and RAG frameworks.
• Foundational experience with AWS or GCP services (e.g., Lambda, S3, or SageMaker).
• Exposure to CI/CD concepts or infrastructure-as-code (e.g., GitHub Actions, Docker).

What's in it for you

• Work on systems that ensure every interaction involves the real human and the right human in an era of accelerating synthetic media and identity manipulation.
• Wake up every day knowing your work has real-world impact by protecting financial institutions and consumers from fraud.
• Gain hands-on experience in a modern environment, working alongside some of the best technical minds in security, AI, and voice intelligence.
• A career-defining opportunity for someone ready to drive meaningful, enterprise-level AI impact.