What are the responsibilities and job description for the Senior AI Engineer position at Siri Infosolutions Inc?
Job Title: Senior AI Engineer
Key Responsibilities
Architect and develop AI-driven IVR and conversational systems using Python
Build NLP models for text classification and clustering to support intent detection and call routing
Perform data analysis using SQL
Design and deploy LLM workflows (prompt engineering, RAG, evaluation) for voice and chat use cases
Lead development of agentic AI workflows for multi-step customer interactions
Establish LLMOps best practices, including monitoring, evaluation, and lifecycle management
Partner with IVR platform, speech engineering, and product teams
Mentor offshore and junior AI engineers
Architect and develop AI-driven IVR and conversational systems using Python
Build NLP models for text classification and clustering to support intent detection and call routing
Perform data analysis using SQL
Design and deploy LLM workflows (prompt engineering, RAG, evaluation) for voice and chat use cases
Lead development of agentic AI workflows for multi-step customer interactions
Establish LLMOps best practices, including monitoring, evaluation, and lifecycle management
Partner with IVR platform, speech engineering, and product teams
Mentor offshore and junior AI engineers
Required Skills & Experience
12 years of experience in AI / ML
Very strong proficiency in Python
Proven expertise in NLP, including:
Text classification
Clustering
Strong experience in data analysis using SQL
Hands-on experience with LLMs:
Prompt engineering
Evaluation frameworks
Retrieval-Augmented Generation (RAG)
12 years of experience in AI / ML
Very strong proficiency in Python
Proven expertise in NLP, including:
Text classification
Clustering
Strong experience in data analysis using SQL
Hands-on experience with LLMs:
Prompt engineering
Evaluation frameworks
Retrieval-Augmented Generation (RAG)
Good to Have
Experience with Agentic AI and multi-agent orchestration
Experience with LLMOps / MLOps in production environments
Cloud Experience
Experience with Agentic AI and multi-agent orchestration
Experience with LLMOps / MLOps in production environments
Cloud Experience
Libraries & Tools
Python / ML: NumPy, Pandas, Scikit-learn, XGBoost
NLP: spaCy, Hugging Face Transformers, NLTK, Sentence-Transformers
LLM Frameworks: LangChain, LlamaIndex, OpenAI SDK
Agentic AI (Good to Have): LangGraph, AutoGen, CrewAI
Data & SQL: Oracle, MySQL, SQLAlchemy
Vector Databases: FAISS, Pinecone, Weaviate, Qdrant
LLMOps / MLOps (Good to Have): MLflow, Weights & Biases, BentoML, Airflow
Python / ML: NumPy, Pandas, Scikit-learn, XGBoost
NLP: spaCy, Hugging Face Transformers, NLTK, Sentence-Transformers
LLM Frameworks: LangChain, LlamaIndex, OpenAI SDK
Agentic AI (Good to Have): LangGraph, AutoGen, CrewAI
Data & SQL: Oracle, MySQL, SQLAlchemy
Vector Databases: FAISS, Pinecone, Weaviate, Qdrant
LLMOps / MLOps (Good to Have): MLflow, Weights & Biases, BentoML, Airflow