Artificial Intelligence Engineer

2 days ago

India Talentgigs Full time

AI Engineer

Location: Chennai Teynampet

Experience: 5+ Years (Hands-On Data Science & AI)

Employment Type: Full-Time

Domain: US Mortgage / Lending Automation

Shift:2pm to 11pm.

About the Role

We are seeking a skilled AI Engineer with deep hands-on experience in ML, NLP, LLMs, GenAI, and Agentic AI to join our technology team focused on automating US mortgage loan processing workflows. This role involves designing intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure.

Key Responsibilities

  • Design and implement ML/NLP/GenAI pipelines for automating loan origination, underwriting, and document intelligence processes.
  • Develop and deploy LLM-based solutions using tools like Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks.
  • Build and orchestrate Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents.
  • Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering.
  • Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models.
  • Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services).
  • Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions.
  • Leverage prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores for contextual mortgage document workflows.

Required Skills & Qualifications

  • 5+ years of hands-on experience in Machine Learning, NLP, or LLM-based systems.
  • Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design.
  • Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers.
  • Strong knowledge of Azure Cloud – including Azure ML, Azure Functions, Azure DevOps.
  • Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow.
  • Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Experience deploying models into production-scale environments.
  • Nice to Have
  • Understanding of US mortgage or lending workflows (1003, 1008,

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