Principal AI/ML Engineer Contact Center Intelligence

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 journeysindependently 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:
  

  • Response generation
    

  • Conversation summarization
    

  • Agent assist and coaching
    

  • Dynamic intent resolution
    

  • Personalized scripting and post-call analytics
    

Contact Center Intelligence & NLP

• Build advanced NLP-powered intelligence features including:
  

  • Intent classification and routing
    

  • Entity extraction
    

  • Sentiment and emotion detection
    

  • Dialogue management
    

  • Multilingual support
    

• 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
    

  • Azure: Azure OpenAI AI Bot Service Cognitive Services Azure ML
    

  • 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)
    

  • MLOps (CI/CD monitoring drift detection scaling)
    

• 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)
    

  • RAG embeddings vector databases (Pinecone Weaviate etc.)
    

  • Voice AI pipelines (ASR TTS spoken dialogue systems)
    

• 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)
  

• Bachelors or Masters 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