NLP Architect - Generative AI & Conversational Intelligence - Remote

1w1 week ago

TMS, LLC

US · Full-time · $250,000 – $350,000

About this role

We are seeking a Principal AI Architect – Generative AI & NLP to lead the design and deployment of next-generation AI platforms powering intelligent customer experiences. This role drives innovation across LLM-based conversational AI, agent assist systems, and autonomous CX workflows. It enables scalable, secure, and human-like interactions across global enterprises.

Define and lead architecture of enterprise-scale LLM-driven conversational AI platforms. Design advanced GraphRAG-based knowledge systems for customer support and agent assist. Architect low-latency inference systems for real-time interactions and build multi-agent AI for autonomous workflows.

Lead and mentor teams of AI engineers, researchers, and architects. Collaborate with product, engineering, and CX teams to deliver AI-powered solutions. Partner with enterprise clients to design custom AI for contact centers.

Work on cutting-edge AI at the intersection of Generative AI and customer experience. Build autonomous AI agents transforming business-customer interactions. Lead innovation in GraphRAG and real-time conversational intelligence, impacting millions globally.

Requirements

15+ years of experience in AI/ML, NLP, or distributed systems
5+ years working with Generative AI and LLM-based systems
Proven experience building production-grade AI platforms at scale
Deep expertise in GraphRAG architecture (not just RAG)
Deep expertise in RLHF and alignment systems
Deep expertise in multi-agent AI systems
Deep expertise in distributed training and inference
Strong programming skills in Python, Scala, or Java

Responsibilities

Define and lead the architecture of enterprise-scale LLM-driven conversational AI platforms
Design advanced RAG and GraphRAG-based knowledge systems for customer support and agent assist
Architect low-latency, high-throughput inference systems for real-time interactions
Build and optimize LLM pipelines, including fine-tuning (LoRA, QLoRA) and prompt orchestration
Develop multi-agent AI systems for autonomous customer workflows and decision intelligence
Develop and deploy RLHF pipelines, guardrails, and hallucination mitigation frameworks
Architect distributed training and inference pipelines across GPU clusters
Lead and mentor teams of AI engineers, researchers, and architects