Principal AI/ML Engineer – Contact Center Intelligence

New York, United States | Posted on 02/03/2026

Location: New York, NY

Hybrid preferred; on‑site collaboration required for key initiatives. Relocation support available for top candidates.

USC and Permanent Residents only

Mandatory Experience = Contact Center Intelligence

Mandatory Total years of experience = 13+ Years

Job Summary

We are hiring a Principal AI/ML Engineer to lead the hands‑on design, development, and scaling of next‑generation AI solutions for contact centers. This is a senior individual contributor role focused on building production‑grade Generative AI and Agentic AI applications tightly integrated with contact center intelligence .

With 15+ years of AI/ML experience (deep focus on NLP and conversational systems) and 2+ years delivering GenAI/Agentic AI in production , you will architect and deploy autonomous, tool‑using, reasoning agents that manage complex customer journeys—independently or in collaboration with human agents. You will work across AWS, Azure, and Google Cloud to deliver scalable, secure, and compliant AI systems that measurably improve containment, CSAT, FCR, and operational efficiency .

Key Responsibilities

Agentic AI & Generative AI Engineering

Design, build, and deploy Agentic AI systems for contact centers, including:

• Multi‑agent orchestration
• Reasoning and planning patterns (ReAct, Plan-and-Execute)
• Tool calling (APIs, CRM systems, knowledge bases)
• Memory management (short‑term and long‑term)
• Self‑correction and feedback loops

Integrate LLMs (GPT‑series, Claude, Llama, Gemini, fine‑tuned open models) into real‑time contact center workflows for:

• Conversation summarization
• Agent assist and coaching
• Dynamic intent resolution
• Personalized scripting and post‑call analytics

Build advanced NLP‑powered intelligence features , including:

• Intent classification and routing
• Entity extraction
• Sentiment and emotion detection

Develop multimodal pipelines (voice + text) using ASR/TTS technologies (e.g., Whisper, Google Speech, Azure Cognitive Services).

Cloud‑Native AI Platforms

Deliver end‑to‑end solutions using major cloud ecosystems:

• AWS: Bedrock, SageMaker, Amazon Connect, Lex/Q, Lambda
• Google Cloud: Vertex AI, Dialogflow CX, Contact Center AI Insights, Gemini models

End‑to‑End AI Lifecycle Ownership

Own the full AI lifecycle:

• Data preparation and feature engineering
• Model selection, fine‑tuning, and prompt engineering
• RAG pipelines and vector search
• Agent framework integration (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel)
• Evaluation (human‑in‑the‑loop, automated metrics)
• Optimize AI systems to directly improve contact center KPIs , including automation rate, AHT reduction, FCR improvement, and proactive engagement

Leadership, Governance & Collaboration

Collaborate with product, engineering, contact center operations, and compliance teams to translate business needs into production‑ready AI capabilities.

Mentor senior engineers, perform code and model reviews, and define best practices.

Ensure responsible AI implementation, including bias mitigation, guardrails, explainability, and safety layers.

Ensure compliance with GDPR, CCPA, TCPA , and voice interaction regulations.

Stay ahead of emerging GenAI and Agentic AI trends; prototype innovations and contribute to internal thought leadership.

Required Qualifications

• 15+ years of professional experience in AI/ML engineering
• 10+ years specializing in NLP and conversational AI systems (chatbots, voice agents, IVR/NLU)
• 2+ years of deep, hands‑on production experience with Generative AI and Agentic AI
• Proven expertise delivering Contact Center Intelligence on AWS, Azure, or Google Cloud
• Strong proficiency in:
  • Python
  • PyTorch, TensorFlow, Hugging Face Transformers
  • Agentic frameworks (LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen)
• Demonstrated impact improving contact center metrics (e.g., 30%+ containment lift , CSAT gains)
• Experience with MLOps (MLflow, Kubeflow, SageMaker Pipelines) and cloud infrastructure (Docker, Kubernetes, serverless )
• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field (PhD a plus )

Preferred Qualifications

• Experience with CCaaS platforms (Genesys, Five9, NICE CXone, Avaya)
• CRM integrations (Salesforce, Dynamics 365 )
• Delivery of multi‑modal, real‑time agentic systems
• Open‑source contributions, publications, or patents in AI/NLP
• Deep knowledge of ethical and responsible AI in regulated environments
• Strong communication and stakeholder influence skills