Principal AI Engineer

NBCUniversal•New York, NY

2d•$220,000 - $265,000

About The Position

We are seeking a Principal AI Engineer with experience bridging research and production of novel AI agents. In this role, you will provide technical leadership in architecting and implementing systems combining symbolic and numerical/data-driven techniques, communicate across functional teams, and ensure architectural choices are well-documented throughout planning and implementation.

Requirements

Graduate degree in Data Science, Computer Science, or a related field (or equivalent deep technical experience).
Proven experience as an AI Engineer or Applied Research Engineer in a fast-paced environment.
Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace is highly valued.
Fluency with Git, and the Unix shell, with a strong ability to work across multiple programming languages as needed (ideally including one or more of Python, C++, C#).
Deep understanding of how to integrate AI agents into production software (e.g., API design, message brokers, and containerization, compute and memory budgeting).
Proven experience building and debugging stochastic AI systems including symbolic AI, procedural generative model, logic programming, and natural language processing.
A strong mathematical background covering logic, linear algebra, probability, and statistics.
Enough ML-adjacent experience to understand model constraints, data requirements, and the "state of the art."

Nice To Haves

Preferred prior experience with modern C++ to interface with data ingestion and product pipelines.
Effective collaboration and the ability to work closely with a founding team.
High attention to detail and the ability to meet key R&D milestones in an early-stage startup environment.
High attention to detail regarding system stability and interoperability.

Responsibilities

Conduct and apply cutting-edge research in AI and natural language processing to solve real-world problems.
Work closely with project leadership across functional domains to understand high-level product vision and translate customer requirements into technical milestones.
Exhibit strong judgement in when to deploy off-the-shelf commercial solutions, customize open-source solutions, or initiate greenfield applied science research projects based on product needs.
Lead by example, amplify team capabilities through intentional coaching & mentorship, foster high-trust/high-performance collaborative attitudes and practices, and establish technical best practices.