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Protocol Intelligence
Data-driven signals on your job's competitivenessTier‑1 brand, mid‑level AI engineer, hybrid metro role and popular LLM title create high candidate competition.
Specialized LLM and production AI skills are transferable, though financial-services experience is a moderate preference.
Explicit 5–8 years, mandatory LLM/production experience and specific tooling requirements indicate high shortlisting strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design, development, and deployment of enterprise-grade AI solutions including Agentic AI frameworks, Retrieval-Augmented Generation (RAG) systems, and intelligent automation platforms.
Architect scalable, secure, and production-ready AI systems with focus on AI governance, observability, security, and operational excellence across Nasdaq.
Collaborate with global stakeholders to translate requirements into AI-powered workflows that improve business outcomes and engineering productivity.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, AI, Engineering, IT, or related field.
5-8 years of software engineering experience with hands-on AI application development.
Proficient in Python and experienced with large language models (LLMs) such as GPT, Claude, Gemini, Llama or similar.
Experience with AI orchestration frameworks like LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, or LlamaIndex.
Ideal Candidate Profile
Proven ability to build and scale Agentic AI architectures, multi-agent systems, and RAG applications using vector databases and knowledge repositories.
Experience integrating AI with enterprise applications, APIs, cloud platforms, and applying AI governance and operational best practices.
Comfortable mentoring engineers, leading adoption of AI engineering standards, and evaluating emerging AI technologies for enterprise use.