AI Engineer - Insurance Domain - HYBRID

Req ID: 368907\n\nNTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.\n\nWe are currently seeking a AI Engineer - Insurance Domain - HYBRID to join our team in Warren, New Jersey (US-NJ), United States (US).\n\nDay to Day Responsibilities:\n\nGenerative AI \u0026 LLM Engineering\n\n * Design, fine-tune, and deploy Large Language Models (LLMs) for insurance-specific use cases including document intelligence, claims summarization, policy interpretation, and underwriting Q\u0026A.\n * Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., Azure AI Search, Pinecone, ChromaDB) to ground LLM outputs in enterprise knowledge bases.\n * Develop prompt engineering frameworks and systematic evaluation pipelines to ensure LLM output quality, consistency, and safety in regulated insurance contexts.\n * Integrate LLM capabilities with internal data platforms via LangChain, LlamaIndex, or Semantic Kernel.\n * Evaluate and benchmark foundational models (OpenAI GPT-4o, Azure OpenAI, Claude, Mistral, Llama) against insurance-specific tasks to guide platform selection.\n\n\n\nAI Agents \u0026 Automation\n\n * Architect and implement autonomous AI agents capable of multi-step reasoning, tool use, and decision-making for workflows such as FNOL triage, claims routing, policy lookup, and compliance checks.\n * Build agentic frameworks using patterns such as ReAct, Chain-of-Thought, and Tool-Augmented Agents to handle complex, multi-turn insurance workflows.\n * Design human-in-the-loop (HITL) checkpoints and escalation logic to ensure AI agents operate within defined risk and compliance boundaries.\n * Integrate agents with internal APIs, data platforms, and enterprise systems using orchestration tools such as Azure Logic Apps, Apache Airflow, or Databricks Workflows.\n * Develop guardrails, monitoring, and audit logging for all deployed agents to meet regulatory and governance standards.\n\n\n\nMLOps \u0026 Model Deployment\n\n * Build and maintain end-to-end MLOps pipelines covering model training, versioning, validation, deployment, and monitoring using MLflow, Azure ML, and Databricks.\n * Implement CI/CD pipelines for ML models using Azure DevOps or GitHub Actions, enabling reliable, repeatable model releases.\n * Deploy models as REST APIs or batch inference services on Azure Kubernetes Service (AKS) or Azure Container Apps, ensuring scalability and low-latency response.\n * Establish model monitoring frameworks to detect data drift, model degradation, and prediction anomalies in production.\n * Manage the model registry and lineage tracking to maintain governance and auditability of all AI assets.\n * Collaborate with data engineering teams to ensure feature pipelines are production-grade, versioned, and integrated with the Feature Store on Databricks or Azure ML.\n\n\n\nCollaboration \u0026 Delivery\n\n * Work closely with business analysts, actuaries, underwriters, and claims professionals to translate domain requirements into AI solution designs.\n * Participate in Agile/Scrum ceremonies including sprint planning, standups, and retrospectives as an active delivery contributor.\n * Produce clear, well-structured technical documentation including solution designs, API specs, model cards, and deployment runbooks.\n * Mentor junior engineers and contribute to internal AI engineering best practices and standards.\n\n\n\nEducation\n\n * Bachelor\u0027s degree in Computer Science, Data Science, Machine Learning, Software Engineering, or a related quantitative field. Master\u0027s degree is a plus.\n\n\n\nMinimum Requirements \n\n * 3+ years of professional experience in AI/ML engineering, with demonstrated delivery of production-grade AI systems.\n * 3+ years hands-on experience building and deploying LLM-powered applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel.\n * 3+ years proven experience implementing MLOps pipelines in cloud environments (Azure preferred).\n * 3+ years experience developing AI agents or automation workflows using agentic frameworks.\n * 2+ years experience in financial services, insurance, or regulated industries is strongly preferred.\n\n\n\nPreferred Qualifications\n\n * Experience with P\u0026C insurance workflows such as FNOL processing, claims triage, underwriting decisioning, or actuarial modeling.\n * Familiarity with insurance regulatory requirements including NAIC guidelines and data privacy standards (CCPA, GDPR).\n * Experience implementing responsible AI principles \u2014 fairness, explainability, and bias mitigation \u2014 in regulated environments.\n * Microsoft certifications: Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100) preferred.\n * Exposure to Data Mesh patterns and publishing AI model outputs as domain data products.\n\n\n\n#LI-NorthAmerica \n\nWhere required by law, NTT DATA provides a reasonable range of compensation for specific roles. The starting pay range for this remote role is $87,120 - $181,500. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate\u2019s actual work location, relevant experience, technical skills, and other qualifications.\n\nAbout NTT DATA\n\nNTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world\u0027s leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R\u0026D.\n\nWhenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client\u2019s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. 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