Production AI Engineer (LLMs, RAG) – Hybrid Atlanta

Nasdaq, Inc.; Atlanta (GA); Hybrid; USD 140,000 - 170,000; Full time

Benefits offered by this job

401(k) match

ESPP discount

Health benefits

Hybrid work schedule

Job summary

Nasdaq, Inc. is seeking an AI Engineer in Atlanta to design and deliver secure, scalable AI-enabled applications for enterprise environments.

You will work with LLMs, RAG, vector search, and agentic workflows to improve search, automation, and decision-making across the business. You will build production-grade software, implement guardrails and safety controls, and collaborate with product and engineering teams to deliver measurable, reliable AI systems.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field or equivalent practical experience.
• 5+ years of software engineering experience with AI/LLM-enabled applications in production environments.
• Experience with RAG architectures, embeddings, vector databases, and cloud AI platforms such as AWS Bedrock or equivalent.

Responsibilities

• Design and build AI-powered applications that use LLMs to improve user workflows, search, automation, and decision support.
• Develop and optimize RAG-based solutions using enterprise data, embeddings, and vector search.
• Integrate AI capabilities through AWS Bedrock or similar platforms, including prompt engineering and safety controls.

Skills

C#

Java

Python

JavaScript/TypeScript

Education

Bachelor's degree in Computer Science, Engineering, AI or related field

Tools

AWS Bedrock

MCP tools

Job description

Nasdaq, Inc. is seeking an AI Engineer in Atlanta to design and deliver secure, scalable AI-enabled applications for enterprise environments.

You will work with LLMs, RAG, vector search, and agentic workflows to improve search, automation, and decision-making across the business. You will build production-grade software, implement guardrails and safety controls, and collaborate with product and engineering teams to deliver measurable, reliable AI systems.