NLP Architect Generative AI & Conversational Intelligence

NLP Architect Generative AI & Conversational Intelligence
Location: Durham, NC (Remote)
Duration: 12+ Months Contract

Job Description:

About the 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 will drive innovation across LLM-based conversational AI, agent assist systems, and autonomous CX workflows, enabling scalable, secure, and human-like interactions across
global enterprises.
You will play a critical role in shaping the future of AI-driven contact center platforms, combining Generative AI, GraphRAG, RLHF, and multi-agent systems to deliver highly
personalized, context-aware, and trustworthy customer interactions.

Required Qualifications:
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:
1. GraphRAG architectures (not just RAG)
2. RLHF and alignment systemsn
3. Multi-agent AI systems
4. Distributed training and inference
Strong programming skills in Python, Scala, or Java
Experience with PyTorch, TensorFlow,Transformers

Key Responsibilities:
AI Architecture & Strategy
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

Generative AI & NLP Systems
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
Implement semantic search, hybrid retrieval, and contextual reasoning systems
Design multimodal AI capabilities (text, voice, chat)
AI Safety, Alignment & Governance
Develop and deploy RLHF pipelines, guardrails, and hallucination mitigation frameworks
Establish Responsible AI practices, including fairness, explainability, and compliance
Lead AI governance frameworks for enterprise deployments
Scalability & Performance Optimization
Architect distributed training and inference pipelines across GPU clusters
Optimize model performance using quantization, mixed precision (FP16/BF16), and MoE architectures
Reduce latency and cost using frameworks like vLLM, Triton, Ray
Leadership & Collaboration
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 and deploy custom AI solutions for contact centers

Note
Education Master s or Ph.D. in Computer Science, AI, Machine Learning, or related field preferred.