Entry level AI Developer (intern)

Position Summary

Precise is excited to launch an entry-level AI Developer position in our Innovation Lab, with select candidates starting as interns with the potential to convert into a full-time role. We will invite exceptional recent graduates or early-career professionals to join us full-time. These candidates may begin with a 3-month paid internship period, with strong performers offered a full-time, permanent position on the team. This is a hands-on opportunity to build real AI solutions alongside visionary tech leads who love to teach and coach. You will move ideas from concept to working prototypes or fully functional applications in days or weeks, not months, using generative AI, agentic AI, machine learning and intelligent automation.

• Must be USC/GC/EAD
• Prefer candidates local to Rockville office but will consider remote

Key Responsibilities:

• Design and build Generative AI applications using large language models (LLMs), prompt engineering and retrieval-augmented generation (RAG).
• Develop agentic AI workflows where AI agents plan, use tools and APIs, and complete multi-step tasks with human oversight.
• Rapidly prototype new ideas, turning concepts into working demos and proofs of concept within short sprint cycles.
• Use AI coding assistants to accelerate development, while reviewing, testing and validating all AI-generated code.
• Apply and enhance machine learning models for real-world use cases, including data preparation, training, evaluation and deployment.
• Identify repetitive business processes and automate them with Robotic Process Automation (RPA), combined with AI for intelligent automation.
• Capture, clean, analyze and validate data from multiple sources, using SQL and NoSQL databases.
• Deploy solutions on cloud platforms such as AWS, Google Cloud or Azure.
• Research emerging AI tools and industry practices, and share findings through demos and presentations.

Projects

Our projects will let you learn and grow skills in Generative AI, agentic AI, rapid prototyping, AI-assisted development, machine learning and RPA. Example areas include:

• AI assistants that answer questions from company knowledge using RAG.
• Multi-agent systems that automate end-to-end workflows such as research, reporting or customer support.
• Intelligent document processing that combines ML, LLMs and RPA to extract and act on data.
• Predictive analytics and ML models that support client and business decisions.
• Rapid innovation sprints that test new AI tools and turn the best ideas into client-ready prototypes.