About this opportunity
bubble lists this Senior Applied AI Engineer opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Requirements
You’ve shipped LLM-powered features in production
You know what makes agents fail
You’re comfortable moving across TypeScript and Python
If that’s you, read on
5+ years of industry experience as a Software or Machine Learning Engineer, or a Master’s/PhD in AI, ML, or NLP with 3+ years of production experience
A track record of shipping LLM-powered features in production—not just API integrations, but real systems with evals, monitoring, and iteration
Hands-on experience building agentic AI workflows and debugging multi-step agent failures
Strong command of RAG, context engineering, and retrieval pipeline design
Experience with transformer models, embeddings, and AI model evaluation
Proficiency in Python for AI/ML work and comfort working in a TypeScript/Node.js codebase
Familiarity with tools like Hugging Face, LangChain, or Mastra
Excellent communication skills and a collaborative, product-minded approach
Alignment with our values: a desire to empower others, a focus on team and user success, and a willingness to experiment and learn from failures
What the job involves
We’re expanding our AI Engineering Team to build next-generation AI‑powered development workflows—enabling users to describe their applications in natural language and have AI generate, modify, and enhance their apps seamlessly
As an Applied AI Engineer, you will help define and ship the future of AI‑powered development at Bubble
This is an engineering role, not a research role
You’ll own LLM‑driven product features end‑to‑end, design agentic workflows that real users depend on, and collaborate closely with Product, Infrastructure, and Research to push the limits of AI‑driven development
Design and build agentic workflows that enable multi‑step AI‑driven app generation for real users at scale
Improve LLM reasoning and retrieval techniques to enhance Bubble’s AI‑powered development tools
Build and maintain production LLM pipelines—including prompt engineering, evaluation frameworks, and latency optimization
Fine‑tune and optimize LLMs for AI‑assisted app‑building workflows using proprietary Bubble datasets
Own AI feature quality end‑to‑end: from prototype through eval, deployment, and monitoring
Work closely with the AI team to scale AI research into production systems
#J-18808-Ljbffr
Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.