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Job Description
Job Description:
- AI Engineer focused on creating scalable LLM and NLP solutions to manage high volumes of customer interactions
- This position will promote architectural best practices and foster innovation within voice AI systems
Key Responsibilities:
- Architect and implement AI-powered IVR and conversational systems utilizing Python
- Develop NLP models for text classification and clustering to enhance intent detection and call routing
- Conduct data analysis with SQL
- Design and deploy LLM workflows, including prompt engineering and RAG evaluation for both voice and chat applications
- Lead the creation of agentic AI workflows for multi-step customer interactions
- Establish best practices for LLMOps, covering monitoring, evaluation, and lifecycle management
- Collaborate with IVR platform teams, speech engineering, and product departments
- Provide mentorship to offshore and junior AI engineers
Technical Requirements:
- Minimum 2 years of experience in AI and ML
- Exceptional proficiency in Python
- Demonstrated expertise in NLP, including
- o Text classification
- o Clustering
- Significant experience in data analysis using SQL
- Practical experience with LLMs
- o Prompt engineering
- o Evaluation frameworks
- o Retrieval Augmented Generation (RAG)
- Good to Have
- Familiarity with Agentic AI and multi-agent orchestration
- Experience with LLMOps and MLOps in production settings
- Cloud experience
- Libraries and Tools
- Python ML, NumPy, Pandas, Scikit-learn, XGBoost
- NLP tools such as spaCy, Hugging Face Transformers, NLTK, and Sentence Transformers
- LLM frameworks like LangChain, LlamaIndex, and OpenAI SDK
- Agentic AI tools (Good to Have), such as LangGraph, AutoGen, and CrewAI
- Data management with SQL, Oracle, MySQL, and SQLAlchemy
- Vector databases including FAISS, Pinecone, Weaviate, and Qdrant
- LLMOps and MLOps tools (Good to Have) such as MLflow, Weights & Biases, BentoML, and Airflow