Urgent Needed - GenAI/ML Engineer - New York, NY - Hybrid

Hi,

 

Our Client is looking for AI/ML Engineer for New York, NY. If you are looking for a job change, please let me know.

 

Job Title: Principal AI/ML Engineer – Generative AI, Agentic AI & Contact Center Intelligence

Location: New York, NY - Hybrid

Job Type: Full-time

 

Job Summary

We are hiring a Principal AI/ML Engineer to lead hands-on development and scaling of next-generation AI solutions for contact centers. This senior individual contributor role focuses on building production-grade Generative AI and Agentic AI applications integrated with contact center intelligence. With 8+ years in AI/ML (heavy emphasis on NLP and conversational systems) and recent 2+ years delivering GenAI/Agentic AI in production, you will design, implement, optimize, and deploy autonomous agents that reason, plan, use tools, and handle complex customer journeys autonomously or in collaboration with human agents. You will work extensively on major cloud platforms (AWS, Azure, Google Cloud) to deliver scalable, secure, compliant solutions that improve containment, CSAT, FCR, and operational efficiency.

 

Key Responsibilities

•  Hands-on design, development, and deployment of Agentic AI systems for contact centers, including multi-agent orchestration, reasoning chains (ReAct, Plan-and-Execute), tool calling (APIs, CRM, knowledge bases), memory management (short-term/long-term), and self-correction mechanisms.

•  Integrate Generative AI (LLMs such as GPT-series, Claude, Llama, Gemini, or fine-tuned open models) into contact center workflows for real-time response generation, conversation summarization, agent assist/coaching, dynamic intent resolution, personalized scripting, and post-call analysis.

•  Build and enhance NLP-powered contact center intelligence features: advanced intent classification, entity extraction, sentiment/emotion detection, dialogue management, multilingual support, and voice/text multimodal pipelines using ASR/TTS (e.g., Whisper, Google Speech, Azure Cognitive Services).

•  Leverage cloud-native services for end-to-end solutions:

            •  AWS: Bedrock, SageMaker, Amazon Connect + Lex/Q, Lambda for agent logic.

            •  Azure: Azure OpenAI, AI Bot Service, Cognitive Services, Azure Machine Learning.

            •  Google Cloud: Vertex AI, Dialogflow CX, Contact Center AI Insights, Gemini models.

•  Own full lifecycle of AI projects: data preparation, model selection/fine-tuning/prompt engineering, RAG implementation, agent framework integration (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel), evaluation (human-in-loop, automated metrics), MLOps (CI/CD, monitoring with PrometheGrafana, drift detection), and production scaling.

•  Optimize for contact center KPIs: increase automation rates, reduce handle time, improve first-contact resolution, and enable proactive/anticipatory interactions via agentic workflows.

•  Collaborate with cross-functional teams (product, engineering, contact center ops, compliance) to translate business requirements into robust, production-ready AI capabilities.

•  Stay ahead of GenAI/Agentic AI advancements; prototype emerging techniques and contribute to internal thought leadership (e.g., tech blogs, internal demos).

Required Qualifications

•  15+ years of professional experience in AI/ML engineering, with 10+ years specializing in NLP and conversational AI systems (chatbots, voice agents, IVR/NLU).

•  At least 2+ years of deep, hands-on production experience building and deploying Generative AI and Agentic AI solutions (autonomous agents, multi-agent systems, tool integration, reasoning/planning, memory orchestration).

•  Proven expertise in Contact Center Intelligence: production deployments on major cloud providers (AWS, Azure, or Google Cloud) using platforms like Amazon Connect/Lex, Google CCA/Dialogflow, Azure Bot Service/OpenAI, or equivalent CCaaS integrations.

•  Strong proficiency in:

            •  Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers).

            •  Agentic frameworks (LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen).

            •  Advanced NLP/GenAI techniques (prompt engineering, fine-tuning/PEFT, RAG, embeddings/vector DBs like Pinecone/Weaviate, evaluation frameworks).

            •  Voice AI pipelines (ASR, TTS, NLU for spoken dialogue).

•  Demonstrated impact delivering measurable improvements in contact center metrics through AI (e.g., 30%+ containment lift, CSAT gains).

•  Experience with MLOps tools (MLflow, Kubeflow, SageMaker Pipelines) and cloud infrastructure (Docker, Kubernetes, serverless).