NLP Architect – Generative AI & Conversational Intelligence

We are looking for a Principal AI Architect – Generative AI & NLP to lead the design and deployment of cutting-edge AI platforms powering intelligent customer experiences.

In this role, you will architect and build LLM-driven conversational AI systems, autonomous AI agents, and next-generation customer interaction platforms using advanced technologies like GraphRAG, RLHF, and multi-agent systems.

This is a high-impact leadership role where you will shape the future of AI-powered contact center and CX platforms at enterprise scale.

 Key Responsibilities:

<>AI Architecture & Strategy

• Define and lead architecture for enterprise-scale LLM-powered conversational AI platforms
• Design advanced RAG / GraphRAG knowledge systems
• Build low-latency, high-throughput inference systems for real-time AI interactions

<>Generative AI & NLP Systems

• Develop and optimize LLM pipelines (fine-tuning: LoRA, QLoRA)
• Build multi-agent AI systems for autonomous workflows
• Implement semantic search, hybrid retrieval, and contextual reasoning
• Design multimodal AI solutions (text, voice, chat)

<>AI Safety, Alignment & Governance

• Implement RLHF pipelines and guardrails
• Design systems for hallucination mitigation & trustworthy AI
• Establish Responsible AI frameworks (fairness, explainability, compliance)

<>Scalability & Performance

• Architect distributed training & inference pipelines across GPU clusters
• Optimize models using quantization, FP16/BF16, MoE architectures
• Improve performance using tools like vLLM, Triton, Ray

<>Leadership & Collaboration

• Lead and mentor teams of AI engineers and architects
• Collaborate with product and CX teams to deliver AI solutions
• Partner with enterprise clients to design scalable AI platforms

Required Qualifications

• 15+ years in AI/ML, NLP, or distributed systems
• 5+ years with Generative AI / LLM systems in production
• Proven experience building scalable AI platforms

<>Core Expertise Required

• GraphRAG architectures
• RLHF & AI alignment systems
• Multi-agent AI systems
• Distributed training & inference

<>Technical Skills

• Strong programming: Python / Java / Scala
• Frameworks: PyTorch, TensorFlow, Transformers