1

Generative Ai Insurance Jobs in Baltimore, MD (NOW HIRING)

AI/ML Engineer

Annapolis Junction, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Familiarity with generative AI models * Experience in edge AI implementation * Expertise in natural ... No cost to you. * Life Insurance - 100% employee coverage. No cost to you. * Additional ...

AI/ML Engineer Level 2

Fort George G Meade, MD

$190K - $205K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with large language models (LLMs), generative AI, or natural language processing ... Benefits Offered : Medical, Dental, Vision, Life Insurance, Short-Term Disability, Long-Term ...

Cleared Hybrid Full Stack AI Developer (5490)

Hanover, MD · On-site +1

$135K - $227K/yr

  • Medical

  • Retirement

  • PTO

Experience with Amazon Bedrock or other enterprise generative AI platforms * Experience ... Some key components of our robust benefits include health insurance, paid leave, and retirement.

Future Opportunities

Columbia, MD · On-site +1

  • Medical

  • Life

  • Retirement

  • PTO

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Benefits: * Health insurance * HSA account * 401(k) with company match * Life & disability ...

SVP, Chief Technology Officer (CTO)

Annapolis, MD · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Lead enterprise implementation of Generative AI, Machine Learning, Intelligent Automation, and ... insurance. * Exceptional executive communication skills with the ability to influence Boards of ...

Showing results 21-40

Generative Ai Insurance information

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 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 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.

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 are popular job titles related to Generative Ai Insurance jobs in Baltimore, MD?

For Generative Ai Insurance jobs in Baltimore, MD, the most frequently searched job titles are:

What cities near Baltimore, MD are hiring for Generative Ai Insurance jobs?

Cities near Baltimore, MD with the most Generative Ai Insurance job openings:

Infographic showing various Generative Ai Insurance job openings in Baltimore, MD as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior AI Engineer with Security Clearance

IntelliGenesis

Annapolis Junction, MD • On-site

$175K - $220K/yr

Other

Medical, Life, Retirement, PTO

Re-posted 21 days ago


Job description

IntelliGenesis Senior AI Engineer IG Labs - Annapolis Junction, MD - Full Time Job Description: 
IntelliGenesis is seeking a Senior AI Engineer to lead the design, development, and deployment of production-grade AI systems supporting mission-critical cyber and intelligence operations. This role focuses on transitioning AI/ML capabilities from concept to operational environments, including classified and resource-constrained settings.  A day in the life includes architecting scalable AI pipelines, deploying models to edge and cloud environments, integrating AI into cybersecurity workflows, and mentoring junior engineers. You will work closely with cyber operators, software engineers, and infrastructure teams to deliver impactful, real-world AI capabilities—not just research prototypes.  The team dynamic is highly collaborative and mission-driven, consisting of AI engineers, cyber SMEs, and platform engineers working in agile sprints. This role serves as a technical leader and mentor, guiding best practices in MLOps, DevSecOps, and secure AI deployment.  What You'll Do:  * Have a direct impact on national security and cyber operations 
* Work on cutting-edge AI systems in fast paced environments 
* Opportunity to lead architecture and influence technical direction 
* Hands-on role across the full AI lifecycle (design → deploy → scale) 
* Strong alignment with DoD modernization and AI initiatives 
* Lead end-to-end AI system design, development, and deployment 
* Architect and implement scalable MLOps pipelines for training, validation, and deployment 
* Deploy AI/ML models to cloud, on-prem, and edge environments 
* Integrate AI capabilities into operational tools and workflows 
* Ensure system security, including adversarial robustness and secure model deployment 
* Collaborate with cross-functional teams (cyber, infrastructure, software engineering) 
* Mentor mid-level engineers and provide technical oversight 
* Rapidly prototype AI solutions and transition them into production systems 
* Ensure compliance with DoD Risk Management Framework (RMF) requirements Required Qualifications:
* Must be a U.S. Citizen
* Active TS/SCI Clearance and Polygraph required 
* 10+ years of experience in AI/ML engineering, software engineering, or related field 
* Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred)
* Strong experience deploying AI/ML models into production environment 
* Expertise in Python and at least one additional language (e.g., C++, Go)
* Experience with MLOps tools (e.g., Kubernetes, Docker, MLflow, Kubeflow)
* Experience with cloud and hybrid infrastructure (AWS, Azure, or DoD cloud environments)
* Knowledge of DevSecOps and infrastructure-as-code (e.g., Terraform, Ansible)
* Experience with model serving, monitoring, and lifecycle management
* Familiarity with cybersecurity concepts and secure system design
* Experience working in classified or regulated environments (DoD/IC preferred) Desired Qualifications:
* Experience with adversarial machine learning and AI security 
* Background in cyber operations or network traffic analysis
* Experience deploying models in edge or disconnected environments
* Familiarity with large language models (LLMs) and generative AI systems
* Knowledge of secure enclaves and confidential computing
* Prior experience supporting DoD or Intelligence Community missions 
* Relevant certifications (e.g., AWS Certified Solutions Architect, Security+, CISSP) 
Compensation Range: $175,000 - $220,000 _____________________________________________________________________________________________________ Compensation ranges encompass a total compensation package and are a general guideline only and not intended as a guaranteed and/or implied final compensation or salary for this job opening. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, candidate’s scope of relevant work experience, educational background, certifications, contract-specific affordability, organizational requirements and alignment with local market data. Our compensation includes other indirect financial components designed to support employees’ total well-being, which should be considered when evaluating our competitive benefits package. These monetary benefits include medical insurance, life insurance, disability, paid time off, maternity/paternity leave, 401(k) company match, training/education reimbursements and other work/life programs. _____________________________________________________________________________________________________ IntelliGenesis is committed to providing equal opportunity to all employees and applicants for employment. The Company is an Equal Opportunity Employer (EOE), and as such, does not tolerate discrimination, retaliation, or harassment of its employees or applicants based upon race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or any other protected characteristic under local, state, or federal law in any employment practice. Such employment practices include, but are not limited to: hiring, promotion, demotion, transfer, recruitment, or recruitment advertising, selection, disciplinary action layoff, termination, rates of pay, or other forms of compensation and selection of training. IntelliGenesis is committed to the fair and equal employment of individuals with disabilities. It is the Company’s policy to reasonably accommodate qualified individuals with disabilities unless the accommodation would impose an undue hardship on the organization. In accordance with the Americans with Disabilities Act (ADA) as amended, reasonable accommodations will be provided to qualified individuals with disabilities, when such accommodations are necessary, to enable them to perform the essential functions of their jobs or to enjoy the equal benefits and privileges of employment. This policy applies to all applicants for employment and all employees.