Senior AI Engineer – AI Platform

We're looking for a highly capable Senior AI Engineer to join our team to build the next generation of AI-powered equity research. This role is hybrid, 3 days in office. You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design.

What You Will Do

You will design, build, and operate core components of our AI platform: distributed agentic workflows, retrieval and reranking systems, model integrations, and the infrastructure required to make these systems reliable, observable, and scalable in production.

Why It Might Be a Fit

A genuine interest in investing, public markets, and fundamental business analysis is expected. You will have direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design.

Requirements

• Bachelor’s degree in Computer Science or equivalent practical experience
• Minimum of 5 years of experience designing, building, and maintaining software systems
• Strong backend expertise in at least one strongly typed language, preferably TypeScript
• Solid understanding of cloud computing primitives, especially AWS
• Strong understanding of agentic AI concepts such as tool use, function calling, state machines or graphs, retrieval and reranking, structured outputs, memory, guardrails, and evaluation
• Experience developing and deploying agentic workflows using frameworks such as LangChain, Mastra, or LangGraph
• Experience shipping and operating multiple GenAI or LLM-powered systems in production
• Hands-on experience debugging scaled LLM systems and participating in incident response
• Experience building RAG pipelines using embeddings and vector databases
• Familiarity with fine-tuning or adapting models for specific tasks
• Experience implementing evaluation pipelines, including human-in-the-loop workflows
• Experience building or maintaining evaluation suites for agentic systems in production

Benefits

• Free onsite fitness center with state-of-the-art equipment, plus daily group classes
• Gourmet cafeteria with daily specials plus soup and salad bars
• Dry cleaning, shoe shining and sneak peeks
• Free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City
• Meaningful and continued investment in data, technology, and product development
• Opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time
• Meaningful exposure to senior leadership and the ability to influence how the platform evolves