Innovative AI Architect

19 hours ago

Amrāvati, Maharashtra, India beBeeArtificialIntelligence Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Artificial Intelligence Engineer

At the forefront of technological innovation, Artificial Intelligence Engineers play a pivotal role in shaping the future.

Our organization seeks an accomplished AI Engineer with profound hands-on expertise in Machine Learning, Natural Language Processing, and Large Language Models to collaborate on automating US mortgage loan processing workflows.

The ideal candidate will possess extensive knowledge in designing intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure.

Key Responsibilities:

  • Design and implement Machine Learning/Natural Language Processing/Agentic AI pipelines for automating loan origination, underwriting, and document intelligence processes.
  • Develop and deploy Large Language Model-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 Large Language Models 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).
  • Collaborate with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions.

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.

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