Interested in this AI/ML Engineer role at National General Insurance?
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About This Role
National General is a part of The Allstate Corporation, which means we have the same innovative drive that keeps us a step ahead of our customers’ evolving needs. We offer home, auto and accident and health insurance, as well as other specialty niche insurance products, through a large network of independent insurance agents, as well as directly to consumers.
Job Description
Company: National General
- National General Insurance is an Allstate company, meaning it operates under the Allstate umbrella while maintaining its own brand identity and specialized insurance products
- This relationship allows National General to leverage Allstate’s resources, technology, and financial stability while continuing to serve its customers with tailored insurance solutions.
- Employee benefits same as that of Allstate US Corporation employees
We are seeking a Senior Consultant II – AI/ML Engineer with a strong .NET engineering foundation and hands\-on experience applying Machine Learning, Generative AI, and LLM technologies in enterprise environments.
This is an applied engineering role focused on designing, building, and integrating AI\-powered solutions into production systems rather than conducting research. The position combines AI/ML work with practical software engineering, data processing, and Azure\-based solution delivery.
Ideal Candidate: A seasoned.NET engineer who has expanded into AI/ML and Generative AI, understands how to operationalize AI within enterprise applications, and can bridge the gap between business needs, data, and production\-ready technology solutions.
What You'll Do
- Design and implement AI\-enabled applications using C\#/.NET, Azure, and modern AI/LLM services.
- Develop data ingestion, transformation, and automation pipelines for structured and unstructured data.
- Build and integrate AI capabilities into existing enterprise applications through APIs and services.
- Partner with business SMEs and technical teams to translate complex business challenges into scalable technical solutions.
- Evaluate, test, and optimize AI/ML outputs for accuracy, reliability, and production readiness.
- Support end\-to\-end delivery, including solution design, implementation, validation, documentation, and production handoff.
Required Qualifications
- Strong software engineering experience with C\#/.NET in enterprise\-scale environments.
- Experience working with Machine Learning, Generative AI, LLMs, or AI\-assisted automation solutions.
- Python and data engineering experience.
- Familiarity with Azure DevOps, CI/CD, observability, and enterprise application support.
- Experience building APIs, integrating applications, and working with structured data, JSON, and SQL databases.
- Hands\-on experience with Azure cloud services and modern application architectures.
- Strong problem\-solving, debugging, and stakeholder communication skills.
- Experience working directly with business users, translating requirements into scalable technical solutions.
Preferred Qualifications
- Experience with Azure OpenAI, GPT\-based solutions, prompt engineering, LangChain/LangGraph, or similar AI frameworks.
- Experience with document processing, data extraction, automation, or intelligent workflow solutions.
- Experience in regulated or large\-scale enterprise environments.
The offered salary range for this role will be in the range of $140,000 to $150,000 annual only.
Skills
Application Development, Artificial Intelligence Markup Language, Azure Devops, Business Model Development, Business Process Development, C Sharp (Programming Language), Data Analytics, Data Engineering, Data Transformation, Enterprise Application, Machine Learning (ML), Microsoft .NET, Microsoft Azure, Microsoft Cloud, Predictive Analytics, Python (Programming Language), Structured Query Language (SQL) Compensation
Compensation offered for this role is 120,000\.00 \- 193,725\.00 annually and is based on experience and qualifications. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact.
Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.
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To view the “EEO Know Your Rights” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs.
To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.
It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.
National General Holdings Corp., a member of the Allstate family of companies, is headquartered in New York City. National General traces its roots to 1939, has a financial strength rating of A– (excellent) from A.M. Best, and provides personal and commercial automobile, homeowners, umbrella, recreational vehicle, motorcycle, supplemental health, and other niche insurance products. We are a specialty personal lines insurance holding company. Through our subsidiaries, we provide a variety of insurance products, including personal and commercial automobile, homeowners, umbrella, recreational vehicle, supplemental health, lender\-placed and other niche insurance products.
Companies \& Partners
Direct General Auto \& Life, Personal Express Insurance, Century\-National Insurance, ABC Insurance Agencies, NatGen Preferred, NatGen Premier, Seattle Specialty, National General Lender Services, ARS, RAC Insurance Partners, Mountain Valley Indemnity, New Jersey Skylands, Adirondack Insurance Exchange, VelaPoint, Quotit, HealthCompare, AHCP, NHIC, Healthcare Solutions Team, North Star Marketing, Euro Accident.
Benefits
National General Holdings Corp. is an Equal Opportunity (EO) employer – Veterans/Disabled and other protected categories. All qualified applicants will receive consideration for employment regardless of any characteristic protected by law. Candidates must possess authorization to work in the United States, as it is not our practice to sponsor individuals for work visas. In the event you need assistance or accommodation in completing your online application, please contact NGIC main office by phone at (336\) 435\-2000\.
Allstate provides a comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse. Employees eligible to work from home also receive a monthly connectivity reimbursement to help offset internet costs.
When working from home, you must have a dedicated, private workspace free from distractions, along with appropriate desk and seating. Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.
Salary Context
This $120K-$193K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At National General Insurance, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($156K) sits 27% below the category median. Disclosed range: $120K to $193K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
National General Insurance AI Hiring
National General Insurance has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $193K - $193K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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