AI Strategist

4 hours ago

Cochin, Kerala, India beBeeArtificialIntelligence Full time ₹ 12,45,816 - ₹ 23,17,819
Job Overview

We are seeking a skilled AI professional to join our team focused on automating US mortgage loan processing workflows.

About the Role

This is an exciting opportunity to design and implement intelligent, scalable solutions using cloud-native MLOps and advanced AI/LLM orchestration tools on Azure.

Key Responsibilities:
  • MLOps Engineer: Design and implement ML/NLP/GenAI pipelines for automating loan origination, underwriting, and document intelligence processes.
  • AI Solution Architect: Develop and deploy LLM-based solutions using tools like Ollama, OpenAI, HuggingFace, and integrate via LangChain or similar frameworks.
  • Agentic AI Specialist: Build and orchestrate Agentic AI systems (e.g., using LangChain Agents, AutoGen, CrewAI) to enable autonomous decision-making, task planning, and loan-processing agents.
  • Domain Expert: Fine-tune domain-specific LLMs and embeddings for intelligent document classification, summarization, and question answering.
  • Deployer: Develop end-to-end MLOps workflows for scalable training, testing, and monitoring of models.
  • Cloud Specialist: Deploy AI models and microservices using Azure (Azure ML, Functions, Blob Storage, App Services).
  • Team Collaborator: Work with cross-functional teams to ensure compliance, explainability, and effectiveness of AI solutions.
Required Skills & Qualifications:
  • Machine Learning Experience: 5+ years of hands-on experience in Machine Learning, NLP, or LLM-based systems.
  • LLM Expertise: Proven expertise with LLMs (e.g., OpenAI, Ollama, GPT-4, Mistral) and LangChain / AutoGen / Agentic AI design.
  • Programming Skills: Proficiency in Python, Scikit-learn, PyTorch/TensorFlow, Spacy, HuggingFace Transformers.
  • Azure Cloud Knowledge: Strong knowledge of Azure Cloud – including Azure ML, Azure Functions, Azure DevOps.
  • MLOps Tools: Experience with MLOps tools like MLflow, Azure ML pipelines, or Kubeflow.
  • Vector Database Familiarity: Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Production Deployment: Experience deploying models into production-scale environments.
  • Nice to Have: Understanding of US mortgage or lending workflows (1003, 1008, bank statements, etc.).
  • Ongoing Professional Development: Exposure to Agentic AI concepts such as autonomous agents, planning, memory chaining.
  • Compliance Awareness: Knowledge of privacy and compliance frameworks (HIPAA, SOC2) in AI deployments.

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