AI Engineer - Generative AI, MLOps, and AI Agents

About the Role

NTT DATA North America is actively seeking talented and driven AI Engineers specializing in Generative AI, MLOps, and AI agent development. This position is remote within India and offers a contract engagement typically ranging from 6 to 12 months with potential extensions. The engineer will develop and deploy AI-driven solutions tailored for property and casualty insurance sectors, collaborating closely with data teams and business units.

Key Responsibilities

• Design, fine-tune, and implement Large Language Models (LLMs) tailored for insurance tasks such as document comprehension, claims summarization, policy analysis, and underwriting queries.
• Build Retrieval-Augmented Generation workflows utilizing vector databases like Azure AI Search, Pinecone, and ChromaDB to anchor LLM responses to enterprise knowledge.
• Create prompt engineering frameworks alongside evaluation procedures to ensure LLM outputs are consistent, accurate, and compliant with insurance regulations.
• Integrate LLMs with internal data platforms using tools like LangChain, LlamaIndex, and Semantic Kernel; benchmark major foundational models to select optimal AI platforms.
• Architect autonomous AI agents capable of multi-step reasoning, tool interoperability, and decision-making, streamlining workflows including first notice of loss (FNOL) triage, claims routing, and compliance tasks.
• Develop agent frameworks employing methodologies like ReAct, Chain-of-Thought, and Tool-Augmented Agents; incorporate human-in-the-loop checks and escalation mechanisms to manage risk and regulatory compliance.
• Interface AI agents with enterprise APIs and orchestration platforms such as Azure Logic Apps, Apache Airflow, and Databricks Workflows; establish comprehensive monitoring, guardrails, and audit logging to uphold governance standards.
• Construct and oversee robust MLOps pipelines covering all phases from training and validation to deployment and monitoring, utilizing MLflow, Azure ML, and Databricks; implement CI/CD pipelines with Azure DevOps or GitHub Actions.
• Deploy models via REST APIs or batch services on platforms like Azure Kubernetes Service (AKS) and Azure Container Apps, ensuring performance and scalability.
• Maintain model governance including registry, lineage tracking, and proactive monitoring for data drift and performance degradation; collaborate with data engineering on feature pipeline production and integration.
• Engage actively in Agile processes, partner with domain experts such as actuaries and underwriters to translate requirements into AI solutions, and document technical designs and operational runbooks.
• Mentor junior team members and contribute to advancing organizational AI engineering standards and practices.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Machine Learning, Software Engineering, or related quantitative fields; master's degree is advantageous.
• At least 3 to 5 years of hands-on experience delivering production-grade AI/ML systems.
• Proficient in developing and deploying LLM-based applications using frameworks including LangChain, LlamaIndex, or Semantic Kernel.
• Experienced with MLOps practices on cloud platforms, preferably Microsoft Azure.
• Skilled in creating autonomous AI agents and automation workflows leveraging agentic frameworks.
• Background in financial services, insurance, or similarly regulated industries is highly preferred.

Technical Expertise

• Generative AI and LLM platforms like OpenAI GPT-4o, Azure OpenAI, Claude, Mistral, Llama 3, Falcon.
• Implementing Retrieval-Augmented Generation architectures with embeddings and vector search technologies.
• Experience with AI agent frameworks such as ReAct, Tool-Augmented Agents, LangGraph, AutoGen, CrewAI.
• Workflow orchestration systems including Apache Airflow, Databricks Workflows, Azure Logic Apps.
• Building and managing MLOps pipelines with MLflow, Azure ML, Docker, Kubernetes (AKS), Azure Container Apps, and continuous delivery using Azure DevOps or GitHub Actions.
• Programming skills in Python (advanced), including libraries like PyTorch, Hugging Face Transformers, scikit-learn, Pandas, and NumPy; SQL proficiency for data manipulation and feature engineering.
• Experience with cloud platforms such as Microsoft Azure services (OpenAI, AI Search, Data Factory) and Databricks ecosystem.

Preferred Experience

• Direct knowledge of property and casualty insurance processes including FNOL, claims triage, underwriting, and actuarial modeling.
• Understanding of insurance regulatory frameworks including NAIC, CCPA, and GDPR compliance.
• Familiarity with responsible AI practices addressing fairness, explainability, and bias mitigation.
• Certifications like Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100) are a plus.
• Exposure to advanced data governance concepts such as Data Mesh and model serving technologies.

About NTT DATA

NTT DATA is a global leader in technology and business services with a $30 billion portfolio, delivering solutions to a majority of Fortune Global 100 companies. The company emphasizes responsible innovation in AI, cloud, security, and digital infrastructure, employing experts worldwide and collaborating with a broad network of partners. NTT DATA is committed to equal opportunity employment and inclusivity.

Additional Notes

This role may require occasional presence at client or company offices depending on business needs despite primarily remote work accommodations. Employment safety includes vigilance against fraudulent recruiter activity; verified communication occurs only via official corporate email domains.