Senior AI Engineer (LLM)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
TL;DR
Senior AI Engineer (LLM/Agentic AI): Building and operating distributed agentic AI systems for AI-powered equity research with an accent on LLM integrations, retrieval and reranking, evaluation, and production reliability. Focus on designing scalable RAG pipelines, debugging complex GenAI systems, and monitoring model quality, cost, drift, and operational health.
Location: Hybrid, 3 days per week at CNBC Headquarters in Englewood Cliffs, New Jersey, United States. External candidates may be required to attend an in-person interview before a hiring decision.
Salary: $140,000β$175,000 per year.
Company
is a publicly traded media company whose StockStory business, part of CNBC, develops AI-powered equity research products for individual investors.
What you will do
- Design, build, deploy, and operate distributed agentic AI workflows and core AI platform components.
- Develop retrieval, reranking, RAG, model integration, and evaluation systems for production use.
- Own complex AI features and subsystems from architecture and implementation through deployment and operations.
- Improve observability, monitoring, alerting, cost tracking, quality measurement, drift detection, and incident response.
- Identify and mitigate performance, bias, alignment, and operational risks in AI systems.
- Collaborate with engineers, analysts, investors, product stakeholders, and senior leadership while contributing to technical standards and team growth.
Requirements
- At least 5 years of software engineering experience building and shipping production systems.
- Strong programming skills in Python and at least one strongly typed language, preferably TypeScript.
- Experience designing and deploying LLM or GenAI systems, including prompting, tool use, RAG, evaluation, and agentic workflows.
- Experience with LangChain, Mastra, or LangGraph, embeddings, vector databases, scalable data pipelines, and large or unstructured datasets.
- Experience with distributed systems, system design, observability, reliability, performance optimization, model lifecycle management, and incident response.
- Bachelorβs degree in Computer Science or equivalent practical experience, plus strong communication skills and demonstrated interest in investing, financial markets, or business analysis.
Culture & Benefits
- Small, high-ownership team with fast execution, autonomy, experimentation, and low bureaucracy.
- Direct collaboration with experienced market professionals, including former hedge fund managers and analysts.
- Free onsite fitness center with equipment and daily group classes.
- Gourmet cafeteria, dry cleaning, shoe shining, and other onsite amenities.
- Free shuttle transportation from multiple locations in Manhattan, Brooklyn, Hoboken, and Jersey City.
- Benefits may include health insurance, retirement plans, and paid time off.
Hiring process
- External candidates may be asked to complete an in-person interview with a Media employee before the hiring decision.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β