AI Engineer
- ITBrainiac Inc.
10 Hours Ago
NA
C2C
Charlotte NC-NC
7-10 Years
Required Skills: AI-driven IVR, voice bots, Conversational AI, Python, MySQL, Oracle
Job Description
AI Engineer – IVR & Conversational AI
Position Overview: We are seeking an experienced AI Engineer with strong IVR and Conversational AI experience to design, develop, integrate, and optimize AI-powered voice and conversational solutions for telecom and customer-service use cases.
Key Responsibilities
· Architect, develop, and enhance AI-driven IVR and conversational AI systems using Python.
· Design AI solutions for voice-based customer interactions, including:
o Intent detection
o Call routing
o Self-service
o Conversational journeys
· Develop and optimize NLP models for intent classification, text classification, clustering, entity recognition, and customer-query understanding.
· Develop LLM-powered workflows for voice and chat applications, including prompt engineering, RAG, evaluation, and response optimization.
· Design conversational AI solutions capable of understanding customer intent and supporting multi-step interactions.
· Integrate AI/ML services with existing IVR, voice, telecom, and backend platforms.
· Work with structured and unstructured data to improve model performance and conversational outcomes.
· Perform data analysis and develop SQL queries using databases such as Oracle and MySQL.
· Develop agentic AI workflows for complex, multi-step customer interactions.
· Implement and evaluate LLM-based solutions using appropriate frameworks and models.
· Establish and follow LLMOps best practices, including monitoring, evaluation, model/prompt lifecycle management, and production performance.
· Collaborate with IVR platform teams, application developers, data engineers, product teams, and business stakeholders.
· Troubleshoot production issues and continuously improve the accuracy, performance, reliability, and scalability of AI-driven customer experiences.
· Participate in architecture discussions, code reviews, testing, deployment, and technical documentation.
Must-Have Skills
IVR & Conversational AI
· Hands-on experience with AI-driven IVR, voice bots, Conversational AI, or contact-center applications.
· Strong understanding of IVR and voice-based customer interaction flows.
· Experience applying AI/NLP for:
o Intent detection
o Call routing
o Classification
o Customer-query understanding
o Conversational experiences
· Experience integrating AI solutions with IVR, voice, telecom, or conversational platforms.
Python & Machine Learning
· Strong hands-on experience with Python.
· Experience with:
o NumPy
o Pandas
o Scikit-learn
o XGBoost
· Strong understanding of machine learning concepts, model development, evaluation, optimization, and production implementation.
NLP
· Strong experience with NLP technologies such as:
o spaCy
o NLTK
o Hugging Face Transformers
o SentenceTransformers
· Experience developing NLP solutions for:
o Classification
o Clustering
o Semantic similarity
o Intent detection
o Text understanding
o Entity recognition
Generative AI / LLM
· Hands-on experience with LLMs and Generative AI.
· Strong knowledge of:
o Prompt Engineering
o Retrieval-Augmented Generation (RAG)
o LLM Evaluation
o Embeddings
o Vector Search
o Semantic Retrieval
o Context Management
· Experience with LangChain and/or LlamaIndex.
· Experience using the OpenAI SDK or comparable LLM APIs.
· Ability to develop and integrate LLM-powered workflows into conversational applications.
Database & Data
· Strong SQL skills.
· Experience with relational databases such as:
o Oracle
o MySQL
· Ability to analyze structured and unstructured data and use insights to improve AI/ML and conversational solutions.
Good-to-Have Skills
· Experience with Agentic AI and multi-agent systems.
· Experience with:
o LangGraph
o AutoGen
o CrewAI
· Telecom, contact-center, voice automation, or customer-service platform experience.
· Experience with speech technologies:
o Speech-to-Text (STT)
o Text-to-Speech (TTS)
· Experience with LLMOps, model monitoring, evaluation frameworks, and production AI lifecycle management.
· AI/ML or Generative AI certifications.
· Experience with enterprise-scale AI applications.
· Experience with CI/CD and production deployment practices.
