Interested in this AI/ML Engineer role at AIG Claims, Inc.?
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About This Role
At AIG, we are reimagining the way we help customers to manage risk. Join us as an Excess Claims, Vice President to play your part in that transformation. It’s an opportunity to grow your skills and experience as a valued member of the team.
Make your mark in Excess Casualty Claims
Our Claims teams are the proven problem solvers of choice for clients, delivering consistent technical excellence and showcasing our service differentiation to create an unparalleled global claims handling experience. Through a robust stakeholder feedback loop and supported by consistent processes and leadership, we take pride in delivering responsive, fair and professional service with empathy and efficiency.
How you will create an impact
As a Vice President in Excess Casualty Claims, you will be responsible for managing a team of five to six claims adjusters who handle severity driven Excess Casualty claims. The claims are mostly General Liability, Premises Liability, Products Liability and Auto Liability in nature. You will be responsible for assigning new claims to adjusters based on workload and claim skill set while you manage and direct adjusters on complex coverage and liability matters, involving evaluations, establishment of reserves and resolution strategy. This includes the approval of coverage position letters. The manager will also handle Customer Service / Account servicing demands and will be required to attend relationship and renewal meetings. You will be instrumental in the training and development of your team and driving best claim practices and achieving AIG goals. Presentations to management and underwriting will be required along with identifying procedural improvements. Strong organizational skills and the ability to multi-task will be critical. Property and Casualty licenses are required. 10 years plus of Excess Casualty claims experience preferred or other related Casualty claims management experience is required.
This position requires:
- Supervision of a team of excess claims adjusters.
- Assist adjuster in determining scope and extent of available primary and excess coverage and review of of appropriate coverage position letters;
- Work with adjuster to development and execution of investigation strategies which identify critical issues effecting liability, causation, and damages;
- Assessing and, as warranted, pursuing risk transfer and contribution opportunities;
- Clear and concise communication and contact with internal and external stakeholders including insureds, brokers, and underwriters;
- Supervise the evaluation of claim exposures and approval of appropriate reserves;
- Effectively managing litigation costs in coordination with counsel, vendors, and insureds.
- Complete monthly and internal claims audit procedures;
- Ensure compliance with all training and best claims practices;
- Recruit, interview and on-board new claims staff.
- Train and develop existing staff and other claims staff within the department in claims skills, coverage review, time management, evaluation, influencing favorable outcomes, and negotiation.
- Present claims and claims issues to senior management;
What you will need to succeed
- 10+ years of Commercial Excess Casualty claims experience preferred; Alternatively management experience in related Casualty claims field.
- Ability to manage a team.
- Excellent communication ability (verbal/written) and strong negotiation skills;
- Advanced experience and capabilities in litigation claims management including ADR and mediation process;
- JD helpful but not required;
- Property and Casualty adjusting licenses required and must be obtained within 6 months;
- Potential for flexible work arrangement
Ready to step up to new challenges? We would love to hear from you.
For positions based in New Jersey and New York, the base salary range is $170,000-$210,000 and the position is eligible for a bonus in accordance with the terms of the applicable incentive plan. In addition, we’re proud to offer a range of competitive benefits, a summary of which can be viewed here:2026 Benefits Overview
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At AIG, we value in-person collaboration as a vital part of our culture, which is why we ask our team members to be primarily in the office. This approach helps us work together effectively and create a supportive, connected environment for our team and clients alike.
Enjoy benefits that take care of what matters
At AIG, our people are our greatest asset. We know how important it is to protect and invest in what’s most important to you. That is why we created our Total Rewards Program, a comprehensive benefits package that extends beyond time spent at work to offer benefits focused on your health, wellbeing and financial security—as well as your professional development—to bring peace of mind to you and your family.
Reimagining insurance to make a bigger difference to the world
American International Group, Inc. (AIG) is a global leader in commercial and personal insurance solutions; we are one of the world’s most far-reaching property casualty networks. It is an exciting time to join us — across our operations, we are thinking in new and innovative ways to deliver ever-better solutions to our customers. At AIG, you can go further to support individuals, businesses, and communities, helping them to manage risk, respond to times of uncertainty and discover new potential. We invest in our largest asset, our people, through continuous learning and development, in a culture that celebrates everyone for who they are and what they want to become.
Welcome to a culture of inclusion
We’re committed to creating a culture that truly respects and celebrates each other’s talents, backgrounds, cultures, opinions and goals. We foster a culture of inclusion and belonging through learning, cultural awareness activities and Employee Resource Groups (ERGs). With global chapters, ERGs are a cornerstone for our culture of inclusion. The talent of our people is one of AIG’s greatest assets, and we are honored that our drive for positive change has been recognized by numerous recent awards and accreditations.
*AIG provides equal opportunity to all qualified individuals regardless of race, color, religion, age, gender, gender expression, national origin, veteran status, disability or any other legally protected categories.*
AIG is committed to working with and providing reasonable accommodations to job applicants and employees with disabilities. If you believe you need a reasonable accommodation, please send an email to candidatecare@aig.com.
Functional Area:
CL - ClaimsAIG Claims, Inc.
Salary Context
This $170K-$210K range is above the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At AIG Claims, Inc., 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 $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($190K) sits 23% above the category median. Disclosed range: $170K to $210K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
AIG Claims, Inc. AI Hiring
AIG Claims, Inc. has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span New York, NY, US, Jersey City, NJ, US. Compensation range: $210K - $210K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national median.
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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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