What is a Product Manager at AIG?

At AIG, the Product Manager role—specifically within the rapidly growing Generative AI and Data Analytics divisions—is a strategic pivot point for the entire organization. You are not simply managing features; you are spearheading a transformation in how one of the world's leading insurance organizations manages risk and serves clients. This role sits at the intersection of complex financial services and cutting-edge technology, tasked with deploying GenAI and advanced analytics to solve intricate business challenges in claims, underwriting, and customer service.

You will be joining a team designed to explore new frontiers. AIG is making significant long-term investments in innovative AI teams to modernize legacy workflows. As a Product Manager here, you are expected to blend best-in-class product management principles with deep technical understanding. You will drive the development of products that streamline operations, such as automating claims processing or enhancing risk assessment models, directly impacting the company’s bottom line and the user experience of millions of policyholders.

This position requires a high degree of ownership. Whether you are focused on GenAI Product Enhancement or acting as a Product Owner for specific AI initiatives, you will lead cross-functional teams of engineers, data scientists, and business stakeholders. You are the bridge between the technical potential of platforms like Palantir Foundry or AWS SageMaker and the practical, regulatory realities of the global insurance market.

Getting Ready for Your Interviews

Preparation for AIG requires a shift in mindset. Unlike pure tech startups where speed is the only metric, AIG values precision, governance, and scalability. Your interviewers want to see that you can innovate within a regulated environment without breaking the trust of the customer.

Focus your preparation on these key evaluation criteria:

GenAI and Technical Fluency – You must demonstrate more than a surface-level understanding of AI. Interviewers will assess your ability to work with data engineering teams and your familiarity with tools like Palantir Foundry, AWS SageMaker, or Snowflake. You need to articulate how AI models move from concept to production deployment.

Agile Execution in Enterprise – AIG relies heavily on structured delivery. You will be evaluated on your mastery of Agile methodologies (Scrum, Kanban) and your ability to manage backlogs and user stories using enterprise-grade platforms like Rally. You must show you can deliver value incrementally while managing scope creep.

Domain Application & Problem Solving – Context is king. You will be tested on your ability to apply technology to insurance-specific problems (e.g., claims, risk management). Even if you lack direct insurance experience, you must demonstrate the ability to learn complex domains quickly and apply product thinking to business-critical workflows.

Stakeholder & Risk Management – In a global financial organization, you cannot build in a silo. You will need to show how you manage conflicting priorities between aggressive engineering goals and conservative legal or compliance requirements. Leadership here means guiding a team through ambiguity while adhering to strict governance standards.

Interview Process Overview

The interview process for Product Management roles at AIG is thorough and structured, designed to assess both your technical competence and your cultural fit within a large, collaborative organization. Typically, the process begins with a recruiter screening to verify your background, particularly your experience with AI/ML products and Agile delivery. This is often followed by a hiring manager interview that digs into your resume and your specific experience with product roadmaps and delivery.

If you pass the initial screens, you will move to a series of panel interviews. These rounds are rigorous and often involve a mix of peers, engineering leads, and business stakeholders. You should expect a slower pace compared to the tech sector; AIG is methodical in its hiring to ensure long-term fit. The focus will shift between your technical knowledge (how you build AI products) and your behavioral competencies (how you handle conflict, deadlines, and governance).

The process is distinctive because of its emphasis on in-person collaboration and governance. You will likely face questions about how you handle "return to office" dynamics and how you manage products that require strict regulatory oversight. Expect the tone to be professional and formal, yet eager to find innovators who can shake up the status quo.

The visual timeline above illustrates the typical flow from application to offer. Note that the "Onsite/Panel Loop" is the most intensive phase, where you will likely meet with 3–5 different interviewers back-to-back. Use the time between the hiring manager screen and the panel loop to deep-dive into AIG’s recent press releases regarding their AI initiatives, as this context will be invaluable during the final rounds.

Deep Dive into Evaluation Areas

To succeed, you must prepare for specific evaluation buckets that AIG prioritizes. Based on the current focus on GenAI and delivery, these are the areas where you will be probed most deeply.

GenAI Product Lifecycle & Strategy

This is the core of the role. Interviewers need to know you can manage a product that is probabilistic (like AI) rather than deterministic. You must understand the difference between a cool demo and a scalable enterprise product.

Be ready to go over:

• Use Case Identification – How you spot opportunities for Generative AI within a business (e.g., summarizing claims documents).
• Model Lifecycle – Understanding the flow from data collection to training, testing, and monitoring in production.
• Success Metrics – How you measure the value of an AI product (accuracy, F1 score) versus business value (time saved, cost reduction).
• Risk & Hallucination – Strategies for mitigating risks associated with Generative AI in a financial context.

Example questions or scenarios:

• "How would you identify a high-value use case for GenAI in the claims adjustment process?"
• "Describe a time you had to pivot a product roadmap because the underlying data or model wasn't performing as expected."
• "How do you determine if a problem requires a GenAI solution versus a traditional rules-based automation?"

Agile Delivery & Execution

AIG uses Rally and follows strict Agile principles. They need "Delivery Managers" who can get things done. This area tests your ability to organize chaos into a structured release plan.

Be ready to go over:

• Backlog Management – Prioritizing features based on business value and technical dependency.
• User Story Creation – Writing detailed requirements and acceptance criteria that engineers can actually code against.
• Ceremony Leadership – Your experience running stand-ups, retrospectives, and sprint planning sessions.
• Release Governance – Managing the rollout of new features, including defect root cause analysis and feedback loops.

Example questions or scenarios:

• "Walk me through how you groom a backlog for a team of 5+ developers."
• "A stakeholder wants to add a feature mid-sprint that risks the delivery timeline. How do you handle this?"
• "How do you ensure your user stories are 'ready for development' before a sprint begins?"

Stakeholder Management in Regulated Industries

You will likely work with people who are not technical. Your ability to translate "AI" into "Business Value" is critical.

Be ready to go over:

• Translation – Explaining complex technical constraints to non-technical business leaders.
• Conflict Resolution – Managing disagreements between data science teams (who want to experiment) and operations teams (who want stability).
• Governance – Adhering to legal and compliance standards during product development.

Example questions or scenarios:

• "Tell me about a time you had to say 'no' to a senior stakeholder. How did you justify it?"
• "How do you manage expectations when an AI model takes longer to train than anticipated?"

Key Responsibilities

As a Product Manager at AIG, your day-to-day work is a blend of strategic planning and tactical execution. You are responsible for the "what" and the "why" of the product, but in this specific Delivery/Enhancement role, you are also heavily involved in the "when" and "how." You will lead a team of internal and external members to develop, test, and deploy GenAI and advanced analytics products.

A significant portion of your week will be spent in Agile ceremonies and tool management. You will manage team activities via the Rally delivery platform, writing and approving user stories, and ensuring that the backlog is healthy and prioritized. You are the gatekeeper for quality, ensuring that every story has the correct acceptance criteria and that the team understands the definition of done.

Beyond execution, you are responsible for the product vision. You will work with users—often internal claims adjusters, underwriters, or risk managers—to understand their pain points. You will translate these needs into a roadmap that leverages AIG’s data assets. You will also oversee the production environment, supporting root cause analysis for defects and ensuring that feedback from the user community is rapidly incorporated into future enhancements.

Role Requirements & Qualifications

AIG is looking for seasoned professionals who can hit the ground running. The bar for experience is relatively high given the complexity of the domain and the technology.

• Experience Level – Typically 10+ years of data & analytics delivery leadership or product management experience is expected for the Manager level, with at least 5+ years for Product Owner roles.
• Technical Skills – Experience with GenAI/AI is a major differentiator. Familiarity with Palantir Foundry, Palantir AIP, Snowflake, or AWS SageMaker is highly valued. You must be comfortable with data engineering concepts.
• Agile Certification – Practical experience with Agile methodologies (Scrum, Kanban) is a must-have. Experience as a Scrum Master or Release Train Engineer is a strong bonus.
• Domain Knowledge – A background in Insurance (Claims/Underwriting) or Financial Services is significantly preferred. Understanding the "business" side of insurance helps you assess value accurately.
• Education – A BA/BS degree is required; an MBA is preferred for higher-level strategic roles.

Must-have skills:

• Proven track record of delivering AI/ML products to market.
• Strong proficiency in Agile tools (Rally, Jira) and processes.
• Ability to write detailed technical user stories and acceptance criteria.
• Data-driven decision-making utilizing metrics to guide product direction.

Nice-to-have skills:

• Deep hands-on development experience in Python or SQL.
• Previous tenure at a large legacy organization undergoing digital transformation.

Common Interview Questions

The questions at AIG will test your ability to operate in a "hybrid" mode: part strategic product thinker, part technical delivery manager. Expect a mix of behavioral questions based on your past experience and hypothetical scenarios related to AI implementation in insurance.

The following questions are representative of the themes you will encounter:

Product & Strategy

• "How do you define a product vision for a technical platform that serves multiple internal business units?"
• "If you were tasked with automating the claims intake process using GenAI, what metrics would you track to ensure success?"
• "How do you prioritize a product backlog when you have competing requests from Legal, Compliance, and Business Operations?"
• "Describe a time you retired a product or feature. How did you manage the user transition?"

Technical & Delivery

• "Explain the difference between a traditional software product lifecycle and an AI/ML product lifecycle."
• "How do you handle a situation where the data science team cannot guarantee the accuracy of a model before a deadline?"
• "Walk us through how you use Rally (or a similar tool) to manage dependencies between teams."
• "What is your approach to testing Generative AI outputs for safety and accuracy?"

Behavioral & Leadership

• "Tell me about a time you had to influence a team that did not report to you to adopt a new process."
• "Describe a situation where a project was going off the rails. What did you do to bring it back on track?"
• "How do you handle a stakeholder who insists on a feature that you know is not technically feasible?"

Frequently Asked Questions

Q: What is the remote work policy for this role? AIG values in-person collaboration as a vital part of their culture. For roles based in Atlanta (and most major hubs), you should expect to be primarily in the office. This is not a fully remote position; the company believes that complex transformation work requires face-to-face interaction.

Q: How technical do I need to be? You do not need to be a coder, but you must be "data literate." You need to understand how AI models work, what data engineering pipelines look like, and the limitations of current GenAI technology. If you cannot discuss the basics of model training or data governance, you will struggle in the interview.

Q: What is the biggest challenge for PMs at AIG? The biggest challenge is often navigating the complexity of a large, regulated organization. You will need to balance the speed of innovation (AI) with the necessary slowness of risk management (Insurance). Success requires patience and excellent stakeholder management skills.

Q: What tools will I be using daily? Expect to live in Rally for agile management. For data and product work, you will likely interface with the Palantir suite (Foundry/AIP) and standard collaboration tools. Familiarity with these specific platforms gives you a significant leg up.

Q: Is insurance experience absolutely required? While it is listed as "preferred," it is highly advantageous. If you do not have insurance experience, you must demonstrate a strong background in another regulated industry (like banking or healthcare) or show an exceptional ability to learn complex domains rapidly.

Other General Tips

Understand the "Why" of GenAI in Insurance: Don't just talk about AI being "cool." Research how AI is specifically transforming insurance—fraud detection, claims automation, and personalized policy pricing. AIG wants to solve business problems, not just build tech.

Refresh on Agile Rigor: AIG mentions "Rally" and "Agile delivery" repeatedly. Be prepared to discuss Agile not just as a buzzword, but as a disciplined practice. Know the difference between a User Story, an Epic, and a Feature.

Demonstrate "Safe Innovation":

Prepare for the Palantir Question:

Be Metric-Oriented: When discussing past projects, always attach a number to your success. "I improved efficiency" is weak. "I reduced claims processing time by 15% using an NLP model" is strong.

Summary & Next Steps

The Product Manager role at AIG offers a rare opportunity to apply the most advanced technology of our time—Generative AI—to one of the most fundamental industries in the global economy. This is a role for a builder who enjoys complexity, values structure, and wants to see their work have a tangible impact on how the world manages risk.

To succeed, focus your preparation on the intersection of Agile delivery, AI technology, and stakeholder management. Review your past experiences and frame them through the lens of delivering value in a complex, regulated environment. Be ready to show how you can lead a team through the ambiguity of building brand-new products.

The salary data provided gives you a baseline for negotiation. At AIG, compensation for this level of role typically includes a base salary, a performance-based annual bonus, and potentially equity or long-term incentives depending on seniority. Ensure you consider the "Total Rewards" package, which AIG highlights as a key part of their offer, including comprehensive health and retirement benefits.

You have the roadmap; now it is time to execute. Approach your preparation with the same rigor you would bring to a product launch. Good luck!