Principal AI/ML Engineer – Contact Center Intelligence
On site interview in NY is mandatory!
Location: New York, NY
(Hybrid preferred; on-site collaboration required for key initiatives. Relocation support available for top candidates.)
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:
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:
Develop multimodal pipelines (voice + text) using ASR/TTS technologies (e.g., Whisper, Google Speech, Azure Cognitive Services)
Cloud-Native AI Platforms
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)
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