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Generative Ai Insurance Jobs in Dallas, TX (NOW HIRING)

Confie

AI Engineer

Addison, TX · On-site +1

$110K - $140K/yr

... pet insurance Purpose Responsible for designing, developing, and deploying production-grade AI solutions including autonomous agents, generative AI applications, and RAG-based systems. You will ...

Morgan Stanley

VP, AI Compliance Officer

Dallas, TX · On-site

$108 - $185/hr

Advise Wealth Management Generative AI and Platforms teams on AI governance, strategy, data usage ... Life Insurance, Disability and other insurance plans, Paid Time Off (including Sick Leave ...

Tata Consultancy Service Limited

AI Architect

Irving, TX · On-site

$150K - $201K/yr

Integrate Generative AI, NLP, and ML models into enterprise applications using Azure OpenAI ... Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional ...

Geico

Staff Engineer - Applied AI

Dallas, TX

Experience building advanced Generative AI capabilities including domain-tuned LLMs, vector reasoning techniques, or specialized retrieval architectures. * Experience with insurance, financial ...

INFOSYS NOVA HOLDINGS LLC

Gen. AI Engineer

Fort Worth, TX · On-site

$97K - $133K/yr

Design and develop enterprise Generative AI applications using LLMs, RAG, Graph RAG, and multi ... care, or Insurance. * Azure, AWS, Google Cloud, or Databricks AI certifications. Technical ...

InterImage

Software Engineer

Arlington, TX · On-site

$85 - $130/hr

Gain hands‑on exposure to cutting‑edge Generative AI capabilities and real‑world applications ... insurance provided, additional voluntary life insurance available InterImage is an Equal ...

AT and T

Lead Data/AI Engineering - Applied AI

Dallas, TX · On-site

$158K - $237K/yr

Generative AI and Evaluation: Develop AI and large language model solutions using patterns such as ... Disability Benefits (short term and long term) * Life and Accidental Death Insurance * Supplemental ...

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Generative Ai Insurance information

What is a Generative AI Insurance professional?

A Generative AI Insurance professional specializes in developing, managing, or implementing generative artificial intelligence solutions within the insurance industry. This role involves using advanced AI models to automate processes such as underwriting, claims processing, risk assessment, and customer service. These professionals work to optimize operations and improve decision-making by leveraging machine learning and data analysis. They also help ensure that AI-driven tools comply with regulatory standards and ethical guidelines.

How does a role in Generative AI Insurance typically collaborate with underwriters and data scientists?

Professionals in Generative AI Insurance often work closely with underwriters to analyze risk profiles and automate policy generation using advanced AI models. Collaboration with data scientists is also essential, as they help develop, test, and refine algorithms that can accurately assess claims, detect fraud, and personalize insurance offerings. This cross-functional teamwork ensures that AI solutions are both technically robust and aligned with industry regulations and business goals, providing opportunities to learn from various experts and contribute to innovative insurance products.

What are the key skills and qualifications needed to thrive as a Generative AI Insurance specialist, and why are they important?

To thrive as a Generative AI Insurance Specialist, you need expertise in data analysis, machine learning, and a solid understanding of insurance products and risk assessment, usually backed by a degree in data science, actuarial science, or a related field. Familiarity with AI development frameworks (such as TensorFlow or PyTorch), insurance-specific analytics platforms, and relevant certifications like CPCU or data science credentials are typically required. Strong problem-solving, communication, and adaptability skills help bridge technical solutions with business needs and client expectations. These competencies ensure innovative, accurate risk modeling and effective implementation of AI solutions within the insurance sector.

What is the difference between Generative Ai Insurance vs Data Scientist?

AspectGenerative Ai InsuranceData Scientist
Required CredentialsTypically requires knowledge of AI, machine learning, insurance policies, and data analysisRequires degrees in computer science, statistics, or related fields; often certifications in data analysis or machine learning
Work EnvironmentInsurance companies, AI firms, or tech departments within insurersTech companies, financial institutions, or insurance firms
Industry UsageDevelops AI models to automate insurance underwriting, claims, and risk assessmentAnalyzes data to extract insights, build predictive models, and inform business decisions

Generative Ai Insurance professionals focus on creating AI systems that generate content or automate insurance processes, while Data Scientists analyze data to inform strategies. Both roles require technical skills but differ in application and industry focus.

What are popular job titles related to Generative Ai Insurance jobs in Dallas, TX?

For Generative Ai Insurance jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Generative Ai Insurance jobs in Dallas, TX look for?

The top searched job categories for Generative Ai Insurance jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Generative Ai Insurance jobs?

Cities near Dallas, TX with the most Generative Ai Insurance job openings:

Generative Ai Insurance jobs near you

Generative AI Leader/Architect

Dallas, TX • On-site, Remote

Tiger Analytics Inc.
Business Management Consulting • 201 - 500 employees
Learn more about Tiger Analytics Inc.external

Full-time

Re-posted 8 days ago

Job description

Tiger Analytics is looking for experienced GenAI Architect to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
We are looking for a hands-on Engineering Lead with deep expertise in Generative AI (GenAI), Large Language Models (LLM) / Small Language Models (SLM) who can lead the design, development, and integration of AI-powered components into real-world, production-grade applications. This role demands strong engineering leadership and best practices, a practical approach to application development and system design with applied AI, fluency in modern AI tools, frameworks, cloud-native application stacks, and preferably knowledge of healthcare domain intricacies. You will lead the technical delivery of AI-powered features for a variety of horizonal and vertical healthcare use cases- all while ensuring compliance with enterprise integration standards.
Requirements
Responsibilities
    • Lead the architecture, design, and implementation of GenAI/Agentic AI based solutions into real-world enterprise-ready applications.
    • Collaborate with AI/ML teams to operationalize models using APIs, embeddings, vector databases, and prompt engineering techniques.
    • Own full-stack development and integration of GenAI features into web/mobile applications.
    • Establish best practices for scalable, secure, and maintainable AI-powered application development.
    • Optimize application performance, latency, and reliability of AI features in production.
    • Drive DevOps practices for continuous delivery and monitoring of AI-enabled services in production.
    • Mentor engineers and guide code reviews, architectural decisions, and DevOps practices.
    • Guide engineering teams in code quality, architectural reviews, and technical mentoring.
    • Evaluate emerging GenAI tools and LLM frameworks (OpenAI, LangChain etc.) and make build-vs-buy recommendations.
    • Oversee application-level development, testing, and deployment.

Requirements
  • 10+ years of full-stack application engineering experience, with at least 2 years leading cross-functional teams.
  • Architect agentic AI systems using LangChain/LangGraph, CrewAI, and OpenAI Agentic SDK
  • Design RAG architectures with hybrid search, vector databases, and knowledge graphs
  • Optimize multi-agent workflows using reinforcement learning, dynamic orchestration, and memory management.
  • Deploy scalable AI solutions on AWS/GCP (SageMaker, Vertex AI, Bedrock API).
  • An Ideal Candidate would be of someone who has-
    8+ years in AI/ML engineering with large-scale deployment expertise.
    Proficient in prompt engineering (zero-shot, chain-of-thought) and LLM evaluation.
    Strong background in insurance/financial domains (preferred)
    Agile collaborator with GitHub/VS Code proficiency

Benefits
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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