Agentic Engineer (New Grad)

Noom US•Princeton, NJ

8d•$75,000 - $85,000•Hybrid

About The Position

Noom is seeking an Agentic Engineer (New Grad) to help build autonomous, AI-driven systems that power innovation across Noom. In this role, you’ll work at the intersection of AI and software engineering, contributing to the development of agent-based workflows that support teams across product, marketing, people, finance, and growth. This is a unique opportunity to join at the ground floor of Noom’s agentic AI journey. You’ll collaborate in small, high-autonomy squads alongside experienced engineers, gaining hands-on experience while making meaningful contributions from day one.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related field (or expected within 6 months)
Strong programming fundamentals in at least one of: Java, Kotlin, or Python
Familiarity with software development practices including Git, code reviews, debugging, and testing
Demonstrated curiosity about AI and language models through coursework, projects, or independent exploration
Strong communication skills and a collaborative mindset in fast-moving, ambiguous environments

Nice To Haves

Experience working with LLM APIs (e.g., OpenAI, Anthropic), including prompt engineering or tool use
Exposure to NLP, machine learning, or language model research through academic or project work
Familiarity with agent orchestration frameworks such as LangGraph, CrewAI, or Autogen
Experience with AI-native developer tools such as Cursor, Codex, or Claude Code
Basic knowledge of cloud platforms (AWS, GCP) or containerization (Docker, Kubernetes)
Contributions to open-source projects, research publications, or standout academic projects

Responsibilities

Contribute to the development of agent-driven systems that translate product requirements into executable specifications and working prototypes
Help implement and iterate on multi-agent coordination workflows supporting cross-functional teams
Write clean, maintainable code to build LLM-powered systems using tools such as OpenAI and Anthropic
Integrate systems with CI/CD pipelines (e.g., GitHub Actions) and support infrastructure-as-code initiatives
Build and improve observability systems, including logging, telemetry, and failure handling for AI workflows
Develop and refine evaluation frameworks for LLM outputs, including automated testing and regression detection
Participate in human-in-the-loop processes to ensure quality and reliability of AI-generated outputs
Collaborate cross-functionally with engineering, data science, and product teams
Stay current with emerging AI models, agent frameworks, and developer tools, sharing insights with the team